Overview

Dataset statistics

Number of variables62
Number of observations83
Missing cells2062
Missing cells (%)40.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.3 KiB
Average record size in memory497.5 B

Variable types

Numeric11
Categorical43
Unsupported8

Alerts

airdate has constant value "2020-12-21" Constant
_embedded.show.dvdCountry.name has constant value "Poland" Constant
_embedded.show.dvdCountry.code has constant value "PL" Constant
_embedded.show.dvdCountry.timezone has constant value "Europe/Warsaw" Constant
_embedded.show.network.officialSite has constant value "https://www.bbc.co.uk/bbctwo" Constant
url has a high cardinality: 83 distinct values High cardinality
name has a high cardinality: 65 distinct values High cardinality
_links.self.href has a high cardinality: 83 distinct values High cardinality
_embedded.show.url has a high cardinality: 56 distinct values High cardinality
_embedded.show.name has a high cardinality: 56 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 54 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 54 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 56 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 56 distinct values High cardinality
id is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
season is highly correlated with number and 3 other fieldsHigh correlation
number is highly correlated with season and 4 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
rating.average is highly correlated with number and 4 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 11 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 6 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with number and 5 other fieldsHigh correlation
id is highly correlated with rating.averageHigh correlation
season is highly correlated with number and 1 other fieldsHigh correlation
number is highly correlated with season and 3 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.externals.tvrage and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with number and 6 other fieldsHigh correlation
id is highly correlated with _embedded.show.idHigh correlation
season is highly correlated with _embedded.show.externals.thetvdbHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
rating.average is highly correlated with number and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with runtime and 6 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
id is highly correlated with url and 26 other fieldsHigh correlation
url is highly correlated with id and 47 other fieldsHigh correlation
name is highly correlated with id and 44 other fieldsHigh correlation
season is highly correlated with url and 29 other fieldsHigh correlation
number is highly correlated with url and 38 other fieldsHigh correlation
type is highly correlated with url and 32 other fieldsHigh correlation
airtime is highly correlated with url and 41 other fieldsHigh correlation
airstamp is highly correlated with url and 46 other fieldsHigh correlation
runtime is highly correlated with url and 43 other fieldsHigh correlation
summary is highly correlated with id and 36 other fieldsHigh correlation
rating.average is highly correlated with url and 30 other fieldsHigh correlation
image.medium is highly correlated with id and 45 other fieldsHigh correlation
image.original is highly correlated with id and 45 other fieldsHigh correlation
_links.self.href is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 36 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with url and 42 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with url and 43 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 39 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.weight is highly correlated with url and 41 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with url and 22 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 47 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with url and 34 other fieldsHigh correlation
number has 3 (3.6%) missing values Missing
runtime has 3 (3.6%) missing values Missing
summary has 74 (89.2%) missing values Missing
rating.average has 79 (95.2%) missing values Missing
image.medium has 69 (83.1%) missing values Missing
image.original has 69 (83.1%) missing values Missing
_embedded.show.language has 1 (1.2%) missing values Missing
_embedded.show.runtime has 9 (10.8%) missing values Missing
_embedded.show.averageRuntime has 1 (1.2%) missing values Missing
_embedded.show.ended has 37 (44.6%) missing values Missing
_embedded.show.officialSite has 9 (10.8%) missing values Missing
_embedded.show.rating.average has 77 (92.8%) missing values Missing
_embedded.show.network has 83 (100.0%) missing values Missing
_embedded.show.webChannel.id has 2 (2.4%) missing values Missing
_embedded.show.webChannel.name has 2 (2.4%) missing values Missing
_embedded.show.webChannel.country.name has 39 (47.0%) missing values Missing
_embedded.show.webChannel.country.code has 39 (47.0%) missing values Missing
_embedded.show.webChannel.country.timezone has 39 (47.0%) missing values Missing
_embedded.show.webChannel.officialSite has 37 (44.6%) missing values Missing
_embedded.show.dvdCountry has 83 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 80 (96.4%) missing values Missing
_embedded.show.externals.thetvdb has 25 (30.1%) missing values Missing
_embedded.show.externals.imdb has 57 (68.7%) missing values Missing
_embedded.show.image.medium has 2 (2.4%) missing values Missing
_embedded.show.image.original has 2 (2.4%) missing values Missing
_embedded.show.summary has 11 (13.3%) missing values Missing
image has 83 (100.0%) missing values Missing
_embedded.show._links.nextepisode.href has 75 (90.4%) missing values Missing
_embedded.show.webChannel.country has 83 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 82 (98.8%) missing values Missing
_embedded.show.dvdCountry.code has 82 (98.8%) missing values Missing
_embedded.show.dvdCountry.timezone has 82 (98.8%) missing values Missing
_embedded.show.image has 83 (100.0%) missing values Missing
_embedded.show.network.id has 79 (95.2%) missing values Missing
_embedded.show.network.name has 79 (95.2%) missing values Missing
_embedded.show.network.country.name has 79 (95.2%) missing values Missing
_embedded.show.network.country.code has 79 (95.2%) missing values Missing
_embedded.show.network.country.timezone has 79 (95.2%) missing values Missing
_embedded.show.network.officialSite has 82 (98.8%) missing values Missing
_embedded.show.webChannel has 83 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.externals.tvrage is uniformly distributed Uniform
_embedded.show.externals.imdb is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
_embedded.show.network.id is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:46:14.952580
Analysis finished2022-09-06 02:46:29.142659
Duration14.19 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2038868.518
Minimum1967930
Maximum2374503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:29.211421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1967930
5-th percentile1973045.9
Q11985222
median1993808
Q32036976.5
95-th percentile2310619.5
Maximum2374503
Range406573
Interquartile range (IQR)51754.5

Descriptive statistics

Standard deviation103946.8004
Coefficient of variation (CV)0.05098259132
Kurtosis3.309026545
Mean2038868.518
Median Absolute Deviation (MAD)11941
Skewness2.067963091
Sum169226087
Variance1.080493732 × 1010
MonotonicityNot monotonic
2022-09-05T21:46:29.338327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19778991
 
1.2%
19985421
 
1.2%
19938171
 
1.2%
19938161
 
1.2%
19938151
 
1.2%
19938141
 
1.2%
19938131
 
1.2%
19938121
 
1.2%
19938111
 
1.2%
19938101
 
1.2%
Other values (73)73
88.0%
ValueCountFrequency (%)
19679301
1.2%
19690631
1.2%
19707681
1.2%
19720591
1.2%
19727131
1.2%
19760421
1.2%
19760431
1.2%
19773291
1.2%
19774161
1.2%
19775781
1.2%
ValueCountFrequency (%)
23745031
1.2%
23682981
1.2%
23539151
1.2%
23539141
1.2%
23181091
1.2%
22432141
1.2%
22396101
1.2%
22111371
1.2%
21975971
1.2%
21972871
1.2%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size792.0 B
https://www.tvmaze.com/episodes/1977899/obycnaa-zensina-2x03-seria-12
 
1
https://www.tvmaze.com/episodes/1998542/love-script-1x03-episode-3
 
1
https://www.tvmaze.com/episodes/1993817/the-case-solver-1x11-episode-11
 
1
https://www.tvmaze.com/episodes/1993816/the-case-solver-1x10-episode-10
 
1
https://www.tvmaze.com/episodes/1993815/the-case-solver-1x09-episode-9
 
1
Other values (78)
78 

Length

Max length141
Median length95
Mean length79.5060241
Min length58

Characters and Unicode

Total characters6599
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1977899/obycnaa-zensina-2x03-seria-12
2nd rowhttps://www.tvmaze.com/episodes/2164195/ispoved-1x09-viktoria-bona
3rd rowhttps://www.tvmaze.com/episodes/1982407/volk-1x09-seria-09
4th rowhttps://www.tvmaze.com/episodes/1982408/volk-1x10-seria-10
5th rowhttps://www.tvmaze.com/episodes/1988014/muzskaa-tema-1x03-seria-3

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1977899/obycnaa-zensina-2x03-seria-121
 
1.2%
https://www.tvmaze.com/episodes/1998542/love-script-1x03-episode-31
 
1.2%
https://www.tvmaze.com/episodes/1993817/the-case-solver-1x11-episode-111
 
1.2%
https://www.tvmaze.com/episodes/1993816/the-case-solver-1x10-episode-101
 
1.2%
https://www.tvmaze.com/episodes/1993815/the-case-solver-1x09-episode-91
 
1.2%
https://www.tvmaze.com/episodes/1993814/the-case-solver-1x08-episode-81
 
1.2%
https://www.tvmaze.com/episodes/1993813/the-case-solver-1x07-episode-71
 
1.2%
https://www.tvmaze.com/episodes/1993812/the-case-solver-1x06-episode-61
 
1.2%
https://www.tvmaze.com/episodes/1993811/the-case-solver-1x05-episode-51
 
1.2%
https://www.tvmaze.com/episodes/1993810/the-case-solver-1x04-episode-41
 
1.2%
Other values (73)73
88.0%

Length

2022-09-05T21:46:29.462385image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1977899/obycnaa-zensina-2x03-seria-121
 
1.2%
https://www.tvmaze.com/episodes/1972059/red-vs-blue-18x07-for-power-pt-11
 
1.2%
https://www.tvmaze.com/episodes/1982407/volk-1x09-seria-091
 
1.2%
https://www.tvmaze.com/episodes/1982408/volk-1x10-seria-101
 
1.2%
https://www.tvmaze.com/episodes/1988014/muzskaa-tema-1x03-seria-31
 
1.2%
https://www.tvmaze.com/episodes/2062926/god-of-ten-thousand-realms-1x01-episode-11
 
1.2%
https://www.tvmaze.com/episodes/2062927/god-of-ten-thousand-realms-1x02-episode-21
 
1.2%
https://www.tvmaze.com/episodes/2062928/god-of-ten-thousand-realms-1x03-episode-31
 
1.2%
https://www.tvmaze.com/episodes/2140388/going-seventeen-2020-12-21-going-vs-seventeen-21
 
1.2%
https://www.tvmaze.com/episodes/2353914/300-year-old-class-of-2020-1x01-episode-11
 
1.2%
Other values (73)73
88.0%

Most occurring characters

ValueCountFrequency (%)
e575
 
8.7%
-537
 
8.1%
s446
 
6.8%
t416
 
6.3%
/415
 
6.3%
o360
 
5.5%
w281
 
4.3%
a247
 
3.7%
p237
 
3.6%
i235
 
3.6%
Other values (30)2850
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4383
66.4%
Decimal Number1015
 
15.4%
Other Punctuation664
 
10.1%
Dash Punctuation537
 
8.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e575
13.1%
s446
 
10.2%
t416
 
9.5%
o360
 
8.2%
w281
 
6.4%
a247
 
5.6%
p237
 
5.4%
i235
 
5.4%
m211
 
4.8%
d195
 
4.4%
Other values (16)1180
26.9%
Decimal Number
ValueCountFrequency (%)
1228
22.5%
2146
14.4%
0134
13.2%
9120
11.8%
395
9.4%
879
 
7.8%
763
 
6.2%
457
 
5.6%
648
 
4.7%
545
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/415
62.5%
.166
 
25.0%
:83
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-537
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4383
66.4%
Common2216
33.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e575
13.1%
s446
 
10.2%
t416
 
9.5%
o360
 
8.2%
w281
 
6.4%
a247
 
5.6%
p237
 
5.4%
i235
 
5.4%
m211
 
4.8%
d195
 
4.4%
Other values (16)1180
26.9%
Common
ValueCountFrequency (%)
-537
24.2%
/415
18.7%
1228
10.3%
.166
 
7.5%
2146
 
6.6%
0134
 
6.0%
9120
 
5.4%
395
 
4.3%
:83
 
3.7%
879
 
3.6%
Other values (4)213
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII6599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e575
 
8.7%
-537
 
8.1%
s446
 
6.8%
t416
 
6.3%
/415
 
6.3%
o360
 
5.5%
w281
 
4.3%
a247
 
3.7%
p237
 
3.6%
i235
 
3.6%
Other values (30)2850
43.2%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct65
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size792.0 B
Episode 2
 
4
Episode 1
 
4
Episode 7
 
3
Episode 4
 
3
Episode 6
 
3
Other values (60)
66 

Length

Max length75
Median length56
Mean length16.73493976
Min length7

Characters and Unicode

Total characters1389
Distinct characters112
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)66.3%

Sample

1st rowСерия 12
2nd rowВиктория Боня
3rd rowСерия 09
4th rowСерия 10
5th rowСерия 3

Common Values

ValueCountFrequency (%)
Episode 24
 
4.8%
Episode 14
 
4.8%
Episode 73
 
3.6%
Episode 43
 
3.6%
Episode 63
 
3.6%
Episode 33
 
3.6%
Episode 52
 
2.4%
Episode 102
 
2.4%
Episode 92
 
2.4%
Episode 82
 
2.4%
Other values (55)55
66.3%

Length

2022-09-05T21:46:29.575308image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode41
 
15.4%
17
 
2.6%
26
 
2.3%
35
 
1.9%
5
 
1.9%
серия5
 
1.9%
the4
 
1.5%
44
 
1.5%
63
 
1.1%
103
 
1.1%
Other values (151)183
68.8%

Most occurring characters

ValueCountFrequency (%)
183
 
13.2%
e96
 
6.9%
o90
 
6.5%
i77
 
5.5%
s70
 
5.0%
d57
 
4.1%
E53
 
3.8%
r50
 
3.6%
a47
 
3.4%
p45
 
3.2%
Other values (102)621
44.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter814
58.6%
Uppercase Letter238
 
17.1%
Space Separator183
 
13.2%
Decimal Number115
 
8.3%
Other Punctuation28
 
2.0%
Dash Punctuation7
 
0.5%
Open Punctuation1
 
0.1%
Close Punctuation1
 
0.1%
Initial Punctuation1
 
0.1%
Final Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e96
11.8%
o90
11.1%
i77
 
9.5%
s70
 
8.6%
d57
 
7.0%
r50
 
6.1%
a47
 
5.8%
p45
 
5.5%
t41
 
5.0%
n26
 
3.2%
Other values (37)215
26.4%
Uppercase Letter
ValueCountFrequency (%)
E53
22.3%
S17
 
7.1%
T16
 
6.7%
L12
 
5.0%
B10
 
4.2%
F9
 
3.8%
N8
 
3.4%
R7
 
2.9%
D7
 
2.9%
С7
 
2.9%
Other values (32)92
38.7%
Decimal Number
ValueCountFrequency (%)
126
22.6%
222
19.1%
016
13.9%
315
13.0%
68
 
7.0%
58
 
7.0%
48
 
7.0%
95
 
4.3%
84
 
3.5%
73
 
2.6%
Other Punctuation
ValueCountFrequency (%)
,10
35.7%
#6
21.4%
:4
 
14.3%
.3
 
10.7%
?2
 
7.1%
'2
 
7.1%
!1
 
3.6%
Space Separator
ValueCountFrequency (%)
183
100.0%
Dash Punctuation
ValueCountFrequency (%)
-7
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Initial Punctuation
ValueCountFrequency (%)
«1
100.0%
Final Punctuation
ValueCountFrequency (%)
»1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin922
66.4%
Common337
 
24.3%
Cyrillic130
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e96
 
10.4%
o90
 
9.8%
i77
 
8.4%
s70
 
7.6%
d57
 
6.2%
E53
 
5.7%
r50
 
5.4%
a47
 
5.1%
p45
 
4.9%
t41
 
4.4%
Other values (37)296
32.1%
Cyrillic
ValueCountFrequency (%)
и15
 
11.5%
я9
 
6.9%
л8
 
6.2%
е7
 
5.4%
р7
 
5.4%
С7
 
5.4%
а5
 
3.8%
к5
 
3.8%
И5
 
3.8%
М4
 
3.1%
Other values (32)58
44.6%
Common
ValueCountFrequency (%)
183
54.3%
126
 
7.7%
222
 
6.5%
016
 
4.7%
315
 
4.5%
,10
 
3.0%
68
 
2.4%
58
 
2.4%
48
 
2.4%
-7
 
2.1%
Other values (13)34
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1257
90.5%
Cyrillic130
 
9.4%
None2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
183
 
14.6%
e96
 
7.6%
o90
 
7.2%
i77
 
6.1%
s70
 
5.6%
d57
 
4.5%
E53
 
4.2%
r50
 
4.0%
a47
 
3.7%
p45
 
3.6%
Other values (58)489
38.9%
Cyrillic
ValueCountFrequency (%)
и15
 
11.5%
я9
 
6.9%
л8
 
6.2%
е7
 
5.4%
р7
 
5.4%
С7
 
5.4%
а5
 
3.8%
к5
 
3.8%
И5
 
3.8%
М4
 
3.1%
Other values (32)58
44.6%
None
ValueCountFrequency (%)
«1
50.0%
»1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct12
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246.3253012
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:29.662500image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)3

Descriptive statistics

Standard deviation660.4837309
Coefficient of variation (CV)2.681347501
Kurtosis3.72828096
Mean246.3253012
Median Absolute Deviation (MAD)0
Skewness2.37449644
Sum20445
Variance436238.7587
MonotonicityNot monotonic
2022-09-05T21:46:29.750301image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
151
61.4%
202010
 
12.0%
25
 
6.0%
45
 
6.0%
34
 
4.8%
182
 
2.4%
91
 
1.2%
301
 
1.2%
71
 
1.2%
121
 
1.2%
Other values (2)2
 
2.4%
ValueCountFrequency (%)
151
61.4%
25
 
6.0%
34
 
4.8%
45
 
6.0%
71
 
1.2%
91
 
1.2%
121
 
1.2%
182
 
2.4%
271
 
1.2%
301
 
1.2%
ValueCountFrequency (%)
202010
12.0%
311
 
1.2%
301
 
1.2%
271
 
1.2%
182
 
2.4%
121
 
1.2%
91
 
1.2%
71
 
1.2%
45
6.0%
34
 
4.8%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct37
Distinct (%)46.2%
Missing3
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean32.8125
Minimum1
Maximum348
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:29.842999image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median10.5
Q331.25
95-th percentile95.35
Maximum348
Range347
Interquartile range (IQR)27.25

Descriptive statistics

Standard deviation65.97738273
Coefficient of variation (CV)2.010739283
Kurtosis13.93105278
Mean32.8125
Median Absolute Deviation (MAD)7.5
Skewness3.720771583
Sum2625
Variance4353.015032
MonotonicityNot monotonic
2022-09-05T21:46:29.951928image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
37
 
8.4%
16
 
7.2%
25
 
6.0%
114
 
4.8%
94
 
4.8%
514
 
4.8%
134
 
4.8%
74
 
4.8%
63
 
3.6%
53
 
3.6%
Other values (27)36
43.4%
ValueCountFrequency (%)
16
7.2%
25
6.0%
37
8.4%
43
3.6%
53
3.6%
63
3.6%
74
4.8%
82
 
2.4%
94
4.8%
103
3.6%
ValueCountFrequency (%)
3481
1.2%
3121
1.2%
3111
1.2%
2351
1.2%
881
1.2%
851
1.2%
701
1.2%
651
1.2%
591
1.2%
531
1.2%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size792.0 B
regular
80 
significant_special
 
2
insignificant_special
 
1

Length

Max length21
Median length7
Mean length7.457831325
Min length7

Characters and Unicode

Total characters619
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular80
96.4%
significant_special2
 
2.4%
insignificant_special1
 
1.2%

Length

2022-09-05T21:46:30.053349image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:30.144389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular80
96.4%
significant_special2
 
2.4%
insignificant_special1
 
1.2%

Most occurring characters

ValueCountFrequency (%)
r160
25.8%
a86
13.9%
e83
13.4%
g83
13.4%
l83
13.4%
u80
12.9%
i13
 
2.1%
n7
 
1.1%
s6
 
1.0%
c6
 
1.0%
Other values (4)12
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter616
99.5%
Connector Punctuation3
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r160
26.0%
a86
14.0%
e83
13.5%
g83
13.5%
l83
13.5%
u80
13.0%
i13
 
2.1%
n7
 
1.1%
s6
 
1.0%
c6
 
1.0%
Other values (3)9
 
1.5%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin616
99.5%
Common3
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
r160
26.0%
a86
14.0%
e83
13.5%
g83
13.5%
l83
13.5%
u80
13.0%
i13
 
2.1%
n7
 
1.1%
s6
 
1.0%
c6
 
1.0%
Other values (3)9
 
1.5%
Common
ValueCountFrequency (%)
_3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII619
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r160
25.8%
a86
13.9%
e83
13.4%
g83
13.4%
l83
13.4%
u80
12.9%
i13
 
2.1%
n7
 
1.1%
s6
 
1.0%
c6
 
1.0%
Other values (4)12
 
1.9%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size792.0 B
2020-12-21
83 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters830
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-21
2nd row2020-12-21
3rd row2020-12-21
4th row2020-12-21
5th row2020-12-21

Common Values

ValueCountFrequency (%)
2020-12-2183
100.0%

Length

2022-09-05T21:46:30.224624image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:30.307463image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-2183
100.0%

Most occurring characters

ValueCountFrequency (%)
2332
40.0%
0166
20.0%
-166
20.0%
1166
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number664
80.0%
Dash Punctuation166
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2332
50.0%
0166
25.0%
1166
25.0%
Dash Punctuation
ValueCountFrequency (%)
-166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common830
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2332
40.0%
0166
20.0%
-166
20.0%
1166
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII830
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2332
40.0%
0166
20.0%
-166
20.0%
1166
20.0%

airtime
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size792.0 B
54 
20:00
16 
10:00
 
4
12:00
 
2
21:00
 
2
Other values (5)
 
5

Length

Max length5
Median length0
Mean length1.746987952
Min length0

Characters and Unicode

Total characters145
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)6.0%

Sample

1st row10:00
2nd row12:00
3rd row
4th row
5th row12:00

Common Values

ValueCountFrequency (%)
54
65.1%
20:0016
 
19.3%
10:004
 
4.8%
12:002
 
2.4%
21:002
 
2.4%
06:001
 
1.2%
18:301
 
1.2%
20:451
 
1.2%
00:001
 
1.2%
19:001
 
1.2%

Length

2022-09-05T21:46:30.391374image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:30.515880image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
20:0016
55.2%
10:004
 
13.8%
12:002
 
6.9%
21:002
 
6.9%
06:001
 
3.4%
18:301
 
3.4%
20:451
 
3.4%
00:001
 
3.4%
19:001
 
3.4%

Most occurring characters

ValueCountFrequency (%)
079
54.5%
:29
 
20.0%
221
 
14.5%
110
 
6.9%
61
 
0.7%
81
 
0.7%
31
 
0.7%
41
 
0.7%
51
 
0.7%
91
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number116
80.0%
Other Punctuation29
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
079
68.1%
221
 
18.1%
110
 
8.6%
61
 
0.9%
81
 
0.9%
31
 
0.9%
41
 
0.9%
51
 
0.9%
91
 
0.9%
Other Punctuation
ValueCountFrequency (%)
:29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common145
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
079
54.5%
:29
 
20.0%
221
 
14.5%
110
 
6.9%
61
 
0.7%
81
 
0.7%
31
 
0.7%
41
 
0.7%
51
 
0.7%
91
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
079
54.5%
:29
 
20.0%
221
 
14.5%
110
 
6.9%
61
 
0.7%
81
 
0.7%
31
 
0.7%
41
 
0.7%
51
 
0.7%
91
 
0.7%

airstamp
Categorical

HIGH CORRELATION

Distinct18
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size792.0 B
2020-12-21T12:00:00+00:00
49 
2020-12-21T17:00:00+00:00
2020-12-21T04:00:00+00:00
2020-12-21T00:00:00+00:00
 
4
2020-12-21T02:00:00+00:00
 
3
Other values (13)
16 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2075
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)13.3%

Sample

1st row2020-12-20T22:00:00+00:00
2nd row2020-12-21T00:00:00+00:00
3rd row2020-12-21T00:00:00+00:00
4th row2020-12-21T00:00:00+00:00
5th row2020-12-21T00:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-21T12:00:00+00:0049
59.0%
2020-12-21T17:00:00+00:006
 
7.2%
2020-12-21T04:00:00+00:005
 
6.0%
2020-12-21T00:00:00+00:004
 
4.8%
2020-12-21T02:00:00+00:003
 
3.6%
2020-12-21T03:00:00+00:003
 
3.6%
2020-12-21T11:00:00+00:002
 
2.4%
2020-12-21T16:00:00+00:001
 
1.2%
2020-12-22T01:00:00+00:001
 
1.2%
2020-12-21T21:00:00+00:001
 
1.2%
Other values (8)8
 
9.6%

Length

2022-09-05T21:46:30.606002image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-21t12:00:00+00:0049
59.0%
2020-12-21t17:00:00+00:006
 
7.2%
2020-12-21t04:00:00+00:005
 
6.0%
2020-12-21t00:00:00+00:004
 
4.8%
2020-12-21t02:00:00+00:003
 
3.6%
2020-12-21t03:00:00+00:003
 
3.6%
2020-12-21t11:00:00+00:002
 
2.4%
2020-12-21t15:00:00+00:001
 
1.2%
2020-12-21t05:00:00+00:001
 
1.2%
2020-12-21t08:00:00+00:001
 
1.2%
Other values (8)8
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0852
41.1%
2391
18.8%
:249
 
12.0%
1228
 
11.0%
-166
 
8.0%
T83
 
4.0%
+83
 
4.0%
76
 
0.3%
46
 
0.3%
34
 
0.2%
Other values (4)7
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1494
72.0%
Other Punctuation249
 
12.0%
Dash Punctuation166
 
8.0%
Uppercase Letter83
 
4.0%
Math Symbol83
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0852
57.0%
2391
26.2%
1228
 
15.3%
76
 
0.4%
46
 
0.4%
34
 
0.3%
53
 
0.2%
92
 
0.1%
61
 
0.1%
81
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:249
100.0%
Dash Punctuation
ValueCountFrequency (%)
-166
100.0%
Uppercase Letter
ValueCountFrequency (%)
T83
100.0%
Math Symbol
ValueCountFrequency (%)
+83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1992
96.0%
Latin83
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0852
42.8%
2391
19.6%
:249
 
12.5%
1228
 
11.4%
-166
 
8.3%
+83
 
4.2%
76
 
0.3%
46
 
0.3%
34
 
0.2%
53
 
0.2%
Other values (3)4
 
0.2%
Latin
ValueCountFrequency (%)
T83
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2075
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0852
41.1%
2391
18.8%
:249
 
12.0%
1228
 
11.0%
-166
 
8.0%
T83
 
4.0%
+83
 
4.0%
76
 
0.3%
46
 
0.3%
34
 
0.2%
Other values (4)7
 
0.3%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct31
Distinct (%)38.8%
Missing3
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean36.6375
Minimum2
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:30.692186image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.95
Q115
median27
Q345
95-th percentile120
Maximum180
Range178
Interquartile range (IQR)30

Descriptive statistics

Standard deviation32.9507664
Coefficient of variation (CV)0.8993726755
Kurtosis5.192923606
Mean36.6375
Median Absolute Deviation (MAD)17
Skewness2.090656178
Sum2931
Variance1085.753006
MonotonicityNot monotonic
2022-09-05T21:46:30.795702image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2712
14.5%
459
 
10.8%
307
 
8.4%
605
 
6.0%
75
 
6.0%
1204
 
4.8%
123
 
3.6%
203
 
3.6%
113
 
3.6%
153
 
3.6%
Other values (21)26
31.3%
(Missing)3
 
3.6%
ValueCountFrequency (%)
22
 
2.4%
42
 
2.4%
52
 
2.4%
75
6.0%
102
 
2.4%
113
3.6%
123
3.6%
153
3.6%
171
 
1.2%
181
 
1.2%
ValueCountFrequency (%)
1801
 
1.2%
1301
 
1.2%
1204
4.8%
901
 
1.2%
605
6.0%
551
 
1.2%
531
 
1.2%
512
 
2.4%
501
 
1.2%
481
 
1.2%

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct9
Distinct (%)100.0%
Missing74
Missing (%)89.2%
Memory size792.0 B
<p>Zero is moments away from achieving the ultimate power! Can Shatter Squad stop him in time? The clocks ticking... </p>
<p>Rachael Ray makes her own Chinese-style pork sausage for her oversized vegetable and protein omelets.</p>
<p>Poetess Yulia Solomonova (Sola Monova) - about modern poetry, poems on the issues of the day, the power of the Internet, inspiration, the throes of creativity, women and men.</p>
<p>Tan and Bun receive a strange visitor, Pat, on the night of his birthday. After a few drinks, Pat reveals his own theories behind Janejira's death. </p>
<p>The three remaining contestants race to the second elimination point where a dramatic change occurs in the race.</p>
Other values (4)

Length

Max length202
Median length121
Mean length140.5555556
Min length94

Characters and Unicode

Total characters1265
Distinct characters57
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row<p>Zero is moments away from achieving the ultimate power! Can Shatter Squad stop him in time? The clocks ticking... </p>
2nd row<p>Rachael Ray makes her own Chinese-style pork sausage for her oversized vegetable and protein omelets.</p>
3rd row<p>Poetess Yulia Solomonova (Sola Monova) - about modern poetry, poems on the issues of the day, the power of the Internet, inspiration, the throes of creativity, women and men.</p>
4th row<p>Tan and Bun receive a strange visitor, Pat, on the night of his birthday. After a few drinks, Pat reveals his own theories behind Janejira's death. </p>
5th row<p>The three remaining contestants race to the second elimination point where a dramatic change occurs in the race.</p>

Common Values

ValueCountFrequency (%)
<p>Zero is moments away from achieving the ultimate power! Can Shatter Squad stop him in time? The clocks ticking... </p>1
 
1.2%
<p>Rachael Ray makes her own Chinese-style pork sausage for her oversized vegetable and protein omelets.</p>1
 
1.2%
<p>Poetess Yulia Solomonova (Sola Monova) - about modern poetry, poems on the issues of the day, the power of the Internet, inspiration, the throes of creativity, women and men.</p>1
 
1.2%
<p>Tan and Bun receive a strange visitor, Pat, on the night of his birthday. After a few drinks, Pat reveals his own theories behind Janejira's death. </p>1
 
1.2%
<p>The three remaining contestants race to the second elimination point where a dramatic change occurs in the race.</p>1
 
1.2%
<p>Heart struggles with a recent breakup.  Jamie finds a connection to a podcaster, Win.  </p>1
 
1.2%
<p>James and Dale meet for the first time under less than favorable circumstances. But things could be looking up.</p>1
 
1.2%
<p>Join Gus Sorola, Gavin Free, Drew Saplin, and Barbara Dunkelman as they discuss Drew's hate for the moon, astrology, climbing very tall mountains and bouncing, and more on this week's RT Podcast!</p>1
 
1.2%
<p>The plague has hit London, and as Christmas approaches, Will and Kate are in wave fifteen of state-enforced home confinement together in Will's London lodgings.</p>1
 
1.2%
(Missing)74
89.2%

Length

2022-09-05T21:46:30.893751image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:31.012784image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
the12
 
6.0%
and9
 
4.5%
a6
 
3.0%
of5
 
2.5%
in4
 
2.0%
on3
 
1.5%
for3
 
1.5%
p3
 
1.5%
time2
 
1.0%
his2
 
1.0%
Other values (143)151
75.5%

Most occurring characters

ValueCountFrequency (%)
189
14.9%
e118
 
9.3%
a87
 
6.9%
n81
 
6.4%
t79
 
6.2%
o76
 
6.0%
i66
 
5.2%
s61
 
4.8%
r58
 
4.6%
h44
 
3.5%
Other values (47)406
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter938
74.2%
Space Separator193
 
15.3%
Uppercase Letter47
 
3.7%
Other Punctuation46
 
3.6%
Math Symbol36
 
2.8%
Dash Punctuation3
 
0.2%
Close Punctuation1
 
0.1%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e118
12.6%
a87
 
9.3%
n81
 
8.6%
t79
 
8.4%
o76
 
8.1%
i66
 
7.0%
s61
 
6.5%
r58
 
6.2%
h44
 
4.7%
p34
 
3.6%
Other values (15)234
24.9%
Uppercase Letter
ValueCountFrequency (%)
S6
12.8%
T5
10.6%
J4
 
8.5%
D4
 
8.5%
P4
 
8.5%
W3
 
6.4%
B3
 
6.4%
R3
 
6.4%
C3
 
6.4%
G2
 
4.3%
Other values (9)10
21.3%
Other Punctuation
ValueCountFrequency (%)
,17
37.0%
.13
28.3%
/9
19.6%
'4
 
8.7%
!2
 
4.3%
?1
 
2.2%
Space Separator
ValueCountFrequency (%)
189
97.9%
 4
 
2.1%
Math Symbol
ValueCountFrequency (%)
<18
50.0%
>18
50.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin985
77.9%
Common280
 
22.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e118
12.0%
a87
 
8.8%
n81
 
8.2%
t79
 
8.0%
o76
 
7.7%
i66
 
6.7%
s61
 
6.2%
r58
 
5.9%
h44
 
4.5%
p34
 
3.5%
Other values (34)281
28.5%
Common
ValueCountFrequency (%)
189
67.5%
<18
 
6.4%
>18
 
6.4%
,17
 
6.1%
.13
 
4.6%
/9
 
3.2%
'4
 
1.4%
 4
 
1.4%
-3
 
1.1%
!2
 
0.7%
Other values (3)3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1261
99.7%
None4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
15.0%
e118
 
9.4%
a87
 
6.9%
n81
 
6.4%
t79
 
6.3%
o76
 
6.0%
i66
 
5.2%
s61
 
4.8%
r58
 
4.6%
h44
 
3.5%
Other values (46)402
31.9%
None
ValueCountFrequency (%)
 4
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing79
Missing (%)95.2%
Memory size792.0 B
10.0
8.0
9.0
8.5

Length

Max length4
Median length3
Mean length3.25
Min length3

Characters and Unicode

Total characters13
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row10.0
2nd row8.0
3rd row9.0
4th row8.5

Common Values

ValueCountFrequency (%)
10.01
 
1.2%
8.01
 
1.2%
9.01
 
1.2%
8.51
 
1.2%
(Missing)79
95.2%

Length

2022-09-05T21:46:31.137828image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:31.227878image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
10.01
25.0%
8.01
25.0%
9.01
25.0%
8.51
25.0%

Most occurring characters

ValueCountFrequency (%)
04
30.8%
.4
30.8%
82
15.4%
11
 
7.7%
91
 
7.7%
51
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number9
69.2%
Other Punctuation4
30.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
04
44.4%
82
22.2%
11
 
11.1%
91
 
11.1%
51
 
11.1%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common13
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
04
30.8%
.4
30.8%
82
15.4%
11
 
7.7%
91
 
7.7%
51
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
04
30.8%
.4
30.8%
82
15.4%
11
 
7.7%
91
 
7.7%
51
 
7.7%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct14
Distinct (%)100.0%
Missing69
Missing (%)83.1%
Memory size792.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/290/726673.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/290/726355.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/288/721860.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/418/1047207.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/290/725070.jpg
Other values (9)

Length

Max length73
Median length72
Mean length72.21428571
Min length72

Characters and Unicode

Total characters1011
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726673.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726355.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721860.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/418/1047207.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/725070.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/290/726673.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726355.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721860.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/418/1047207.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725070.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/407/1018198.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725463.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725468.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/417/1044221.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725475.jpg1
 
1.2%
Other values (4)4
 
4.8%
(Missing)69
83.1%

Length

2022-09-05T21:46:31.308759image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/290/726673.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726355.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721860.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/418/1047207.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725070.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/407/1018198.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725463.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725468.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/417/1044221.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725475.jpg1
 
7.1%
Other values (4)4
28.6%

Most occurring characters

ValueCountFrequency (%)
/98
 
9.7%
a84
 
8.3%
s70
 
6.9%
m70
 
6.9%
t70
 
6.9%
p56
 
5.5%
e56
 
5.5%
i42
 
4.2%
c42
 
4.2%
.42
 
4.2%
Other values (22)381
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter714
70.6%
Other Punctuation154
 
15.2%
Decimal Number129
 
12.8%
Connector Punctuation14
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a84
11.8%
s70
9.8%
m70
9.8%
t70
9.8%
p56
 
7.8%
e56
 
7.8%
i42
 
5.9%
c42
 
5.9%
d42
 
5.9%
l28
 
3.9%
Other values (8)154
21.6%
Decimal Number
ValueCountFrequency (%)
223
17.8%
720
15.5%
014
10.9%
813
10.1%
912
9.3%
111
8.5%
411
8.5%
59
 
7.0%
68
 
6.2%
38
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/98
63.6%
.42
27.3%
:14
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin714
70.6%
Common297
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a84
11.8%
s70
9.8%
m70
9.8%
t70
9.8%
p56
 
7.8%
e56
 
7.8%
i42
 
5.9%
c42
 
5.9%
d42
 
5.9%
l28
 
3.9%
Other values (8)154
21.6%
Common
ValueCountFrequency (%)
/98
33.0%
.42
14.1%
223
 
7.7%
720
 
6.7%
014
 
4.7%
_14
 
4.7%
:14
 
4.7%
813
 
4.4%
912
 
4.0%
111
 
3.7%
Other values (4)36
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1011
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/98
 
9.7%
a84
 
8.3%
s70
 
6.9%
m70
 
6.9%
t70
 
6.9%
p56
 
5.5%
e56
 
5.5%
i42
 
4.2%
c42
 
4.2%
.42
 
4.2%
Other values (22)381
37.7%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct14
Distinct (%)100.0%
Missing69
Missing (%)83.1%
Memory size792.0 B
https://static.tvmaze.com/uploads/images/original_untouched/290/726673.jpg
https://static.tvmaze.com/uploads/images/original_untouched/290/726355.jpg
https://static.tvmaze.com/uploads/images/original_untouched/288/721860.jpg
https://static.tvmaze.com/uploads/images/original_untouched/418/1047207.jpg
https://static.tvmaze.com/uploads/images/original_untouched/290/725070.jpg
Other values (9)

Length

Max length75
Median length74
Mean length74.21428571
Min length74

Characters and Unicode

Total characters1039
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726673.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726355.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721860.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/418/1047207.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/725070.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726673.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726355.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/288/721860.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/418/1047207.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/725070.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/407/1018198.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/725463.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/725468.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/417/1044221.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/725475.jpg1
 
1.2%
Other values (4)4
 
4.8%
(Missing)69
83.1%

Length

2022-09-05T21:46:31.393072image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726673.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/290/726355.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/288/721860.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/418/1047207.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/290/725070.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/407/1018198.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/290/725463.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/290/725468.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/417/1044221.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/290/725475.jpg1
 
7.1%
Other values (4)4
28.6%

Most occurring characters

ValueCountFrequency (%)
/98
 
9.4%
t84
 
8.1%
a70
 
6.7%
s56
 
5.4%
i56
 
5.4%
o56
 
5.4%
p42
 
4.0%
c42
 
4.0%
.42
 
4.0%
g42
 
4.0%
Other values (23)451
43.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter742
71.4%
Other Punctuation154
 
14.8%
Decimal Number129
 
12.4%
Connector Punctuation14
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t84
 
11.3%
a70
 
9.4%
s56
 
7.5%
i56
 
7.5%
o56
 
7.5%
p42
 
5.7%
c42
 
5.7%
g42
 
5.7%
m42
 
5.7%
e42
 
5.7%
Other values (9)210
28.3%
Decimal Number
ValueCountFrequency (%)
223
17.8%
720
15.5%
014
10.9%
813
10.1%
912
9.3%
111
8.5%
411
8.5%
59
 
7.0%
68
 
6.2%
38
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/98
63.6%
.42
27.3%
:14
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin742
71.4%
Common297
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t84
 
11.3%
a70
 
9.4%
s56
 
7.5%
i56
 
7.5%
o56
 
7.5%
p42
 
5.7%
c42
 
5.7%
g42
 
5.7%
m42
 
5.7%
e42
 
5.7%
Other values (9)210
28.3%
Common
ValueCountFrequency (%)
/98
33.0%
.42
14.1%
223
 
7.7%
720
 
6.7%
:14
 
4.7%
_14
 
4.7%
014
 
4.7%
813
 
4.4%
912
 
4.0%
111
 
3.7%
Other values (4)36
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/98
 
9.4%
t84
 
8.1%
a70
 
6.7%
s56
 
5.4%
i56
 
5.4%
o56
 
5.4%
p42
 
4.0%
c42
 
4.0%
.42
 
4.0%
g42
 
4.0%
Other values (23)451
43.4%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size792.0 B
https://api.tvmaze.com/episodes/1977899
 
1
https://api.tvmaze.com/episodes/1998542
 
1
https://api.tvmaze.com/episodes/1993817
 
1
https://api.tvmaze.com/episodes/1993816
 
1
https://api.tvmaze.com/episodes/1993815
 
1
Other values (78)
78 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3237
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977899
2nd rowhttps://api.tvmaze.com/episodes/2164195
3rd rowhttps://api.tvmaze.com/episodes/1982407
4th rowhttps://api.tvmaze.com/episodes/1982408
5th rowhttps://api.tvmaze.com/episodes/1988014

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19778991
 
1.2%
https://api.tvmaze.com/episodes/19985421
 
1.2%
https://api.tvmaze.com/episodes/19938171
 
1.2%
https://api.tvmaze.com/episodes/19938161
 
1.2%
https://api.tvmaze.com/episodes/19938151
 
1.2%
https://api.tvmaze.com/episodes/19938141
 
1.2%
https://api.tvmaze.com/episodes/19938131
 
1.2%
https://api.tvmaze.com/episodes/19938121
 
1.2%
https://api.tvmaze.com/episodes/19938111
 
1.2%
https://api.tvmaze.com/episodes/19938101
 
1.2%
Other values (73)73
88.0%

Length

2022-09-05T21:46:31.479866image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19778991
 
1.2%
https://api.tvmaze.com/episodes/19720591
 
1.2%
https://api.tvmaze.com/episodes/19824071
 
1.2%
https://api.tvmaze.com/episodes/19824081
 
1.2%
https://api.tvmaze.com/episodes/19880141
 
1.2%
https://api.tvmaze.com/episodes/20629261
 
1.2%
https://api.tvmaze.com/episodes/20629271
 
1.2%
https://api.tvmaze.com/episodes/20629281
 
1.2%
https://api.tvmaze.com/episodes/21403881
 
1.2%
https://api.tvmaze.com/episodes/23539141
 
1.2%
Other values (73)73
88.0%

Most occurring characters

ValueCountFrequency (%)
/332
 
10.3%
p249
 
7.7%
s249
 
7.7%
e249
 
7.7%
t249
 
7.7%
o166
 
5.1%
a166
 
5.1%
i166
 
5.1%
.166
 
5.1%
m166
 
5.1%
Other values (16)1079
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2075
64.1%
Other Punctuation581
 
17.9%
Decimal Number581
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p249
12.0%
s249
12.0%
e249
12.0%
t249
12.0%
o166
8.0%
a166
8.0%
i166
8.0%
m166
8.0%
h83
 
4.0%
d83
 
4.0%
Other values (3)249
12.0%
Decimal Number
ValueCountFrequency (%)
9109
18.8%
197
16.7%
869
11.9%
260
10.3%
752
9.0%
352
9.0%
043
 
7.4%
439
 
6.7%
633
 
5.7%
527
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/332
57.1%
.166
28.6%
:83
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2075
64.1%
Common1162
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/332
28.6%
.166
14.3%
9109
 
9.4%
197
 
8.3%
:83
 
7.1%
869
 
5.9%
260
 
5.2%
752
 
4.5%
352
 
4.5%
043
 
3.7%
Other values (3)99
 
8.5%
Latin
ValueCountFrequency (%)
p249
12.0%
s249
12.0%
e249
12.0%
t249
12.0%
o166
8.0%
a166
8.0%
i166
8.0%
m166
8.0%
h83
 
4.0%
d83
 
4.0%
Other values (3)249
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/332
 
10.3%
p249
 
7.7%
s249
 
7.7%
e249
 
7.7%
t249
 
7.7%
o166
 
5.1%
a166
 
5.1%
i166
 
5.1%
.166
 
5.1%
m166
 
5.1%
Other values (16)1079
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct56
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44844.14458
Minimum802
Maximum63310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:31.579516image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum802
5-th percentile6147
Q144736.5
median52479
Q352655
95-th percentile59481.6
Maximum63310
Range62508
Interquartile range (IQR)7918.5

Descriptive statistics

Standard deviation16372.02223
Coefficient of variation (CV)0.3650871789
Kurtosis1.133158404
Mean44844.14458
Median Absolute Deviation (MAD)2283
Skewness-1.549344993
Sum3722064
Variance268043112
MonotonicityNot monotonic
2022-09-05T21:46:31.694579image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5265512
 
14.5%
524795
 
6.0%
545413
 
3.6%
521812
 
2.4%
521592
 
2.4%
521042
 
2.4%
627642
 
2.4%
528982
 
2.4%
525242
 
2.4%
547622
 
2.4%
Other values (46)49
59.0%
ValueCountFrequency (%)
8021
1.2%
25041
1.2%
60901
1.2%
61461
1.2%
61472
2.4%
72411
1.2%
98151
1.2%
152502
2.4%
175841
1.2%
189711
1.2%
ValueCountFrequency (%)
633101
1.2%
627642
2.4%
617551
1.2%
595551
1.2%
588211
1.2%
584261
1.2%
583671
1.2%
570091
1.2%
566551
1.2%
547622
2.4%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct56
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Memory size792.0 B
https://www.tvmaze.com/shows/52655/the-case-solver
12 
https://www.tvmaze.com/shows/52479/beauty-and-the-boss
 
5
https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realms
 
3
https://www.tvmaze.com/shows/52181/volk
 
2
https://www.tvmaze.com/shows/52159/to-love
 
2
Other values (51)
59 

Length

Max length67
Median length61
Mean length51.10843373
Min length39

Characters and Unicode

Total characters4242
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)51.8%

Sample

1st rowhttps://www.tvmaze.com/shows/39115/obycnaa-zensina
2nd rowhttps://www.tvmaze.com/shows/48683/ispoved
3rd rowhttps://www.tvmaze.com/shows/52181/volk
4th rowhttps://www.tvmaze.com/shows/52181/volk
5th rowhttps://www.tvmaze.com/shows/52520/muzskaa-tema

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52655/the-case-solver12
 
14.5%
https://www.tvmaze.com/shows/52479/beauty-and-the-boss5
 
6.0%
https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realms3
 
3.6%
https://www.tvmaze.com/shows/52181/volk2
 
2.4%
https://www.tvmaze.com/shows/52159/to-love2
 
2.4%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.4%
https://www.tvmaze.com/shows/62764/300-year-old-class-of-20202
 
2.4%
https://www.tvmaze.com/shows/52898/legend-of-yun-qian2
 
2.4%
https://www.tvmaze.com/shows/52524/forever-love2
 
2.4%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
2.4%
Other values (46)49
59.0%

Length

2022-09-05T21:46:31.804447image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52655/the-case-solver12
 
14.5%
https://www.tvmaze.com/shows/52479/beauty-and-the-boss5
 
6.0%
https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realms3
 
3.6%
https://www.tvmaze.com/shows/52524/forever-love2
 
2.4%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.4%
https://www.tvmaze.com/shows/52781/love-script2
 
2.4%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
2.4%
https://www.tvmaze.com/shows/6147/rooster-teeth-animated-adventures2
 
2.4%
https://www.tvmaze.com/shows/52898/legend-of-yun-qian2
 
2.4%
https://www.tvmaze.com/shows/62764/300-year-old-class-of-20202
 
2.4%
Other values (46)49
59.0%

Most occurring characters

ValueCountFrequency (%)
/415
 
9.8%
t355
 
8.4%
w351
 
8.3%
s341
 
8.0%
o258
 
6.1%
e249
 
5.9%
h215
 
5.1%
m191
 
4.5%
a178
 
4.2%
-168
 
4.0%
Other values (30)1521
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2988
70.4%
Other Punctuation664
 
15.7%
Decimal Number422
 
9.9%
Dash Punctuation168
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t355
11.9%
w351
11.7%
s341
11.4%
o258
8.6%
e249
8.3%
h215
 
7.2%
m191
 
6.4%
a178
 
6.0%
v117
 
3.9%
c116
 
3.9%
Other values (16)617
20.6%
Decimal Number
ValueCountFrequency (%)
5104
24.6%
261
14.5%
450
11.8%
645
10.7%
142
10.0%
030
 
7.1%
727
 
6.4%
924
 
5.7%
824
 
5.7%
315
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/415
62.5%
.166
 
25.0%
:83
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2988
70.4%
Common1254
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t355
11.9%
w351
11.7%
s341
11.4%
o258
8.6%
e249
8.3%
h215
 
7.2%
m191
 
6.4%
a178
 
6.0%
v117
 
3.9%
c116
 
3.9%
Other values (16)617
20.6%
Common
ValueCountFrequency (%)
/415
33.1%
-168
13.4%
.166
 
13.2%
5104
 
8.3%
:83
 
6.6%
261
 
4.9%
450
 
4.0%
645
 
3.6%
142
 
3.3%
030
 
2.4%
Other values (4)90
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII4242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/415
 
9.8%
t355
 
8.4%
w351
 
8.3%
s341
 
8.0%
o258
 
6.1%
e249
 
5.9%
h215
 
5.1%
m191
 
4.5%
a178
 
4.2%
-168
 
4.0%
Other values (30)1521
35.9%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct56
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Memory size792.0 B
The Case Solver
12 
Beauty and the Boss
 
5
God of Ten Thousand Realms
 
3
Волк
 
2
To Love
 
2
Other values (51)
59 

Length

Max length33
Median length26
Mean length16.31325301
Min length4

Characters and Unicode

Total characters1354
Distinct characters90
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)51.8%

Sample

1st rowОбычная женщина
2nd rowИсповедь
3rd rowВолк
4th rowВолк
5th rowМужская тема

Common Values

ValueCountFrequency (%)
The Case Solver12
 
14.5%
Beauty and the Boss5
 
6.0%
God of Ten Thousand Realms3
 
3.6%
Волк2
 
2.4%
To Love2
 
2.4%
Twisted Fate of Love2
 
2.4%
300 Year-Old Class of 20202
 
2.4%
Legend of Yun Qian2
 
2.4%
Forever Love2
 
2.4%
Youths in the Breeze2
 
2.4%
Other values (46)49
59.0%

Length

2022-09-05T21:46:31.902780image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the25
 
10.0%
of13
 
5.2%
case12
 
4.8%
solver12
 
4.8%
love8
 
3.2%
and6
 
2.4%
beauty5
 
2.0%
boss5
 
2.0%
ten4
 
1.6%
god3
 
1.2%
Other values (123)157
62.8%

Most occurring characters

ValueCountFrequency (%)
167
 
12.3%
e153
 
11.3%
o77
 
5.7%
a71
 
5.2%
s63
 
4.7%
t59
 
4.4%
n56
 
4.1%
r52
 
3.8%
h47
 
3.5%
T43
 
3.2%
Other values (80)566
41.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter927
68.5%
Uppercase Letter236
 
17.4%
Space Separator167
 
12.3%
Decimal Number16
 
1.2%
Other Punctuation6
 
0.4%
Dash Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e153
16.5%
o77
 
8.3%
a71
 
7.7%
s63
 
6.8%
t59
 
6.4%
n56
 
6.0%
r52
 
5.6%
h47
 
5.1%
d43
 
4.6%
i41
 
4.4%
Other values (40)265
28.6%
Uppercase Letter
ValueCountFrequency (%)
T43
18.2%
S24
 
10.2%
C19
 
8.1%
B17
 
7.2%
R16
 
6.8%
A13
 
5.5%
L13
 
5.5%
M11
 
4.7%
W11
 
4.7%
Y9
 
3.8%
Other values (21)60
25.4%
Other Punctuation
ValueCountFrequency (%)
.2
33.3%
'2
33.3%
/1
16.7%
,1
16.7%
Decimal Number
ValueCountFrequency (%)
09
56.2%
24
25.0%
33
 
18.8%
Space Separator
ValueCountFrequency (%)
167
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1072
79.2%
Common191
 
14.1%
Cyrillic91
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e153
 
14.3%
o77
 
7.2%
a71
 
6.6%
s63
 
5.9%
t59
 
5.5%
n56
 
5.2%
r52
 
4.9%
h47
 
4.4%
T43
 
4.0%
d43
 
4.0%
Other values (41)408
38.1%
Cyrillic
ValueCountFrequency (%)
н8
 
8.8%
е8
 
8.8%
а8
 
8.8%
о6
 
6.6%
к5
 
5.5%
и5
 
5.5%
т4
 
4.4%
В4
 
4.4%
п4
 
4.4%
я3
 
3.3%
Other values (20)36
39.6%
Common
ValueCountFrequency (%)
167
87.4%
09
 
4.7%
24
 
2.1%
33
 
1.6%
.2
 
1.0%
-2
 
1.0%
'2
 
1.0%
/1
 
0.5%
,1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1261
93.1%
Cyrillic91
 
6.7%
None2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
167
 
13.2%
e153
 
12.1%
o77
 
6.1%
a71
 
5.6%
s63
 
5.0%
t59
 
4.7%
n56
 
4.4%
r52
 
4.1%
h47
 
3.7%
T43
 
3.4%
Other values (48)473
37.5%
Cyrillic
ValueCountFrequency (%)
н8
 
8.8%
е8
 
8.8%
а8
 
8.8%
о6
 
6.6%
к5
 
5.5%
и5
 
5.5%
т4
 
4.4%
В4
 
4.4%
п4
 
4.4%
я3
 
3.3%
Other values (20)36
39.6%
None
ValueCountFrequency (%)
ø1
50.0%
Ç1
50.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size792.0 B
Scripted
50 
Talk Show
Animation
Reality
Documentary
 
3
Other values (4)

Length

Max length11
Median length8
Mean length8.024096386
Min length4

Characters and Unicode

Total characters666
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st rowScripted
2nd rowDocumentary
3rd rowScripted
4th rowScripted
5th rowTalk Show

Common Values

ValueCountFrequency (%)
Scripted50
60.2%
Talk Show9
 
10.8%
Animation7
 
8.4%
Reality6
 
7.2%
Documentary3
 
3.6%
News3
 
3.6%
Variety2
 
2.4%
Sports2
 
2.4%
Game Show1
 
1.2%

Length

2022-09-05T21:46:31.997531image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:32.108089image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted50
53.8%
show10
 
10.8%
talk9
 
9.7%
animation7
 
7.5%
reality6
 
6.5%
documentary3
 
3.2%
news3
 
3.2%
variety2
 
2.2%
sports2
 
2.2%
game1
 
1.1%

Most occurring characters

ValueCountFrequency (%)
i72
10.8%
t70
10.5%
e65
9.8%
S62
9.3%
r57
8.6%
c53
 
8.0%
p52
 
7.8%
d50
 
7.5%
a28
 
4.2%
o22
 
3.3%
Other values (17)135
20.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter563
84.5%
Uppercase Letter93
 
14.0%
Space Separator10
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i72
12.8%
t70
12.4%
e65
11.5%
r57
10.1%
c53
9.4%
p52
9.2%
d50
8.9%
a28
 
5.0%
o22
 
3.9%
n17
 
3.0%
Other values (8)77
13.7%
Uppercase Letter
ValueCountFrequency (%)
S62
66.7%
T9
 
9.7%
A7
 
7.5%
R6
 
6.5%
D3
 
3.2%
N3
 
3.2%
V2
 
2.2%
G1
 
1.1%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin656
98.5%
Common10
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i72
11.0%
t70
10.7%
e65
9.9%
S62
9.5%
r57
8.7%
c53
8.1%
p52
7.9%
d50
 
7.6%
a28
 
4.3%
o22
 
3.4%
Other values (16)125
19.1%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i72
10.8%
t70
10.5%
e65
9.8%
S62
9.3%
r57
8.6%
c53
 
8.0%
p52
 
7.8%
d50
 
7.5%
a28
 
4.2%
o22
 
3.3%
Other values (17)135
20.3%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)18.3%
Missing1
Missing (%)1.2%
Memory size792.0 B
Chinese
33 
English
19 
Russian
Korean
Norwegian
Other values (10)
12 

Length

Max length10
Median length7
Mean length6.963414634
Min length4

Characters and Unicode

Total characters571
Distinct characters30
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)9.8%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
Chinese33
39.8%
English19
22.9%
Russian9
 
10.8%
Korean5
 
6.0%
Norwegian4
 
4.8%
Thai2
 
2.4%
Tagalog2
 
2.4%
Japanese1
 
1.2%
Polish1
 
1.2%
Spanish1
 
1.2%
Other values (5)5
 
6.0%

Length

2022-09-05T21:46:32.202898image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chinese33
40.2%
english19
23.2%
russian9
 
11.0%
korean5
 
6.1%
norwegian4
 
4.9%
thai2
 
2.4%
tagalog2
 
2.4%
japanese1
 
1.2%
polish1
 
1.2%
spanish1
 
1.2%
Other values (5)5
 
6.1%

Most occurring characters

ValueCountFrequency (%)
e77
13.5%
n75
13.1%
i74
13.0%
s74
13.0%
h59
10.3%
C33
5.8%
a32
5.6%
g27
 
4.7%
l22
 
3.9%
E19
 
3.3%
Other values (20)79
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter489
85.6%
Uppercase Letter82
 
14.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e77
15.7%
n75
15.3%
i74
15.1%
s74
15.1%
h59
12.1%
a32
6.5%
g27
 
5.5%
l22
 
4.5%
u12
 
2.5%
o12
 
2.5%
Other values (8)25
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
C33
40.2%
E19
23.2%
R9
 
11.0%
T5
 
6.1%
K5
 
6.1%
N4
 
4.9%
L2
 
2.4%
J1
 
1.2%
P1
 
1.2%
S1
 
1.2%
Other values (2)2
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin571
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e77
13.5%
n75
13.1%
i74
13.0%
s74
13.0%
h59
10.3%
C33
5.8%
a32
5.6%
g27
 
4.7%
l22
 
3.9%
E19
 
3.3%
Other values (20)79
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII571
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e77
13.5%
n75
13.1%
i74
13.0%
s74
13.0%
h59
10.3%
C33
5.8%
a32
5.6%
g27
 
4.7%
l22
 
3.9%
E19
 
3.3%
Other values (20)79
13.8%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size792.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size792.0 B
Ended
46 
Running
32 
To Be Determined

Length

Max length16
Median length5
Mean length6.43373494
Min length5

Characters and Unicode

Total characters534
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowEnded
3rd rowEnded
4th rowEnded
5th rowEnded

Common Values

ValueCountFrequency (%)
Ended46
55.4%
Running32
38.6%
To Be Determined5
 
6.0%

Length

2022-09-05T21:46:32.300798image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:32.390339image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ended46
49.5%
running32
34.4%
to5
 
5.4%
be5
 
5.4%
determined5
 
5.4%

Most occurring characters

ValueCountFrequency (%)
n147
27.5%
d97
18.2%
e66
12.4%
E46
 
8.6%
i37
 
6.9%
R32
 
6.0%
u32
 
6.0%
g32
 
6.0%
10
 
1.9%
T5
 
0.9%
Other values (6)30
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter431
80.7%
Uppercase Letter93
 
17.4%
Space Separator10
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n147
34.1%
d97
22.5%
e66
15.3%
i37
 
8.6%
u32
 
7.4%
g32
 
7.4%
o5
 
1.2%
t5
 
1.2%
r5
 
1.2%
m5
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
E46
49.5%
R32
34.4%
T5
 
5.4%
B5
 
5.4%
D5
 
5.4%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin524
98.1%
Common10
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n147
28.1%
d97
18.5%
e66
12.6%
E46
 
8.8%
i37
 
7.1%
R32
 
6.1%
u32
 
6.1%
g32
 
6.1%
T5
 
1.0%
o5
 
1.0%
Other values (5)25
 
4.8%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII534
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n147
27.5%
d97
18.2%
e66
12.4%
E46
 
8.6%
i37
 
6.9%
R32
 
6.0%
u32
 
6.0%
g32
 
6.0%
10
 
1.9%
T5
 
0.9%
Other values (6)30
 
5.6%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct22
Distinct (%)29.7%
Missing9
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean39.75675676
Minimum2
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:32.465167image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.65
Q120
median34
Q349.5
95-th percentile120
Maximum180
Range178
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation33.53706223
Coefficient of variation (CV)0.8435562898
Kurtosis4.491310929
Mean39.75675676
Median Absolute Deviation (MAD)15
Skewness1.897165363
Sum2942
Variance1124.734543
MonotonicityNot monotonic
2022-09-05T21:46:32.558082image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3412
14.5%
459
10.8%
308
9.6%
607
8.4%
75
 
6.0%
104
 
4.8%
204
 
4.8%
1204
 
4.8%
503
 
3.6%
22
 
2.4%
Other values (12)16
19.3%
(Missing)9
10.8%
ValueCountFrequency (%)
22
 
2.4%
42
 
2.4%
52
 
2.4%
75
6.0%
104
4.8%
121
 
1.2%
152
 
2.4%
204
4.8%
221
 
1.2%
231
 
1.2%
ValueCountFrequency (%)
1801
 
1.2%
1301
 
1.2%
1204
 
4.8%
901
 
1.2%
607
8.4%
512
 
2.4%
503
 
3.6%
481
 
1.2%
459
10.8%
3412
14.5%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)32.9%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean36.80487805
Minimum2
Maximum181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:32.649783image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q115
median30
Q345
95-th percentile118.9
Maximum181
Range179
Interquartile range (IQR)30

Descriptive statistics

Standard deviation32.33407369
Coefficient of variation (CV)0.8785268532
Kurtosis5.335767185
Mean36.80487805
Median Absolute Deviation (MAD)15
Skewness2.053397468
Sum3018
Variance1045.492322
MonotonicityNot monotonic
2022-09-05T21:46:32.748459image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3019
22.9%
459
10.8%
606
 
7.2%
75
 
6.0%
154
 
4.8%
104
 
4.8%
204
 
4.8%
254
 
4.8%
503
 
3.6%
1203
 
3.6%
Other values (17)21
25.3%
ValueCountFrequency (%)
22
 
2.4%
42
 
2.4%
52
 
2.4%
75
6.0%
91
 
1.2%
104
4.8%
111
 
1.2%
122
 
2.4%
141
 
1.2%
154
4.8%
ValueCountFrequency (%)
1811
 
1.2%
1301
 
1.2%
1203
3.6%
981
 
1.2%
901
 
1.2%
771
 
1.2%
606
7.2%
503
3.6%
481
 
1.2%
471
 
1.2%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct45
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size792.0 B
2020-12-21
21 
2020-12-14
2020-12-07
 
4
2020-11-23
 
3
2011-09-28
 
2
Other values (40)
45 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters830
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)42.2%

Sample

1st row2018-10-29
2nd row2020-05-11
3rd row2020-12-07
4th row2020-12-07
5th row2020-12-17

Common Values

ValueCountFrequency (%)
2020-12-2121
25.3%
2020-12-148
 
9.6%
2020-12-074
 
4.8%
2020-11-233
 
3.6%
2011-09-282
 
2.4%
2020-11-192
 
2.4%
2020-12-202
 
2.4%
2013-12-242
 
2.4%
2020-11-302
 
2.4%
2020-12-132
 
2.4%
Other values (35)35
42.2%

Length

2022-09-05T21:46:32.842558image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2121
25.3%
2020-12-148
 
9.6%
2020-12-074
 
4.8%
2020-11-233
 
3.6%
2013-12-242
 
2.4%
2020-12-132
 
2.4%
2020-11-302
 
2.4%
2020-12-202
 
2.4%
2020-11-192
 
2.4%
2011-09-282
 
2.4%
Other values (35)35
42.2%

Most occurring characters

ValueCountFrequency (%)
2219
26.4%
0195
23.5%
-166
20.0%
1155
18.7%
921
 
2.5%
418
 
2.2%
317
 
2.0%
712
 
1.4%
812
 
1.4%
59
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number664
80.0%
Dash Punctuation166
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2219
33.0%
0195
29.4%
1155
23.3%
921
 
3.2%
418
 
2.7%
317
 
2.6%
712
 
1.8%
812
 
1.8%
59
 
1.4%
66
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
-166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common830
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2219
26.4%
0195
23.5%
-166
20.0%
1155
18.7%
921
 
2.5%
418
 
2.2%
317
 
2.0%
712
 
1.4%
812
 
1.4%
59
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII830
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2219
26.4%
0195
23.5%
-166
20.0%
1155
18.7%
921
 
2.5%
418
 
2.2%
317
 
2.0%
712
 
1.4%
812
 
1.4%
59
 
1.1%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct18
Distinct (%)39.1%
Missing37
Missing (%)44.6%
Memory size792.0 B
2022-05-02
12 
2021-01-18
2020-12-28
2021-01-25
2020-12-31
Other values (13)
17 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters460
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)19.6%

Sample

1st row2021-01-07
2nd row2022-08-30
3rd row2020-12-28
4th row2020-12-28
5th row2020-12-25

Common Values

ValueCountFrequency (%)
2022-05-0212
 
14.5%
2021-01-187
 
8.4%
2020-12-285
 
6.0%
2021-01-253
 
3.6%
2020-12-312
 
2.4%
2020-12-222
 
2.4%
2021-01-052
 
2.4%
2020-12-302
 
2.4%
2020-12-232
 
2.4%
2021-01-071
 
1.2%
Other values (8)8
 
9.6%
(Missing)37
44.6%

Length

2022-09-05T21:46:32.924687image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-05-0212
26.1%
2021-01-187
15.2%
2020-12-285
10.9%
2021-01-253
 
6.5%
2020-12-312
 
4.3%
2020-12-222
 
4.3%
2021-01-052
 
4.3%
2020-12-302
 
4.3%
2020-12-232
 
4.3%
2021-02-221
 
2.2%
Other values (8)8
17.4%

Most occurring characters

ValueCountFrequency (%)
2156
33.9%
0112
24.3%
-92
20.0%
156
 
12.2%
518
 
3.9%
813
 
2.8%
37
 
1.5%
63
 
0.7%
72
 
0.4%
41
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number368
80.0%
Dash Punctuation92
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2156
42.4%
0112
30.4%
156
 
15.2%
518
 
4.9%
813
 
3.5%
37
 
1.9%
63
 
0.8%
72
 
0.5%
41
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common460
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2156
33.9%
0112
24.3%
-92
20.0%
156
 
12.2%
518
 
3.9%
813
 
2.8%
37
 
1.5%
63
 
0.7%
72
 
0.4%
41
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2156
33.9%
0112
24.3%
-92
20.0%
156
 
12.2%
518
 
3.9%
813
 
2.8%
37
 
1.5%
63
 
0.7%
72
 
0.4%
41
 
0.2%

_embedded.show.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct50
Distinct (%)67.6%
Missing9
Missing (%)10.8%
Memory size792.0 B
https://www.iqiyi.com/a_c4m3iuc94t.html
12 
https://programme.mytvsuper.com/tc/130336/
 
5
https://v.qq.com/detail/m/mzc002007995z4v.html
 
3
https://premier.one/show/12339
 
2
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=1
 
2
Other values (45)
50 

Length

Max length105
Median length77
Mean length49.10810811
Min length18

Characters and Unicode

Total characters3634
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)54.1%

Sample

1st rowhttps://premier.one/show/8405
2nd rowhttps://premier.one/collections/134
3rd rowhttps://premier.one/show/12339
4th rowhttps://premier.one/show/12339
5th rowhttps://www.ivi.ru/watch/muzhskaya-tema

Common Values

ValueCountFrequency (%)
https://www.iqiyi.com/a_c4m3iuc94t.html12
 
14.5%
https://programme.mytvsuper.com/tc/130336/5
 
6.0%
https://v.qq.com/detail/m/mzc002007995z4v.html3
 
3.6%
https://premier.one/show/123392
 
2.4%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
2.4%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.4%
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
2.4%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.4%
https://www.tytnetwork.com2
 
2.4%
https://roosterteeth.com/series/rt-animated-adventures2
 
2.4%
Other values (40)40
48.2%
(Missing)9
 
10.8%

Length

2022-09-05T21:46:33.025845image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.iqiyi.com/a_c4m3iuc94t.html12
 
16.2%
https://programme.mytvsuper.com/tc/1303365
 
6.8%
https://v.qq.com/detail/m/mzc002007995z4v.html3
 
4.1%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
2.7%
https://www.tytnetwork.com2
 
2.7%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.7%
https://roosterteeth.com/series/rt-animated-adventures2
 
2.7%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.7%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
2.7%
https://premier.one/show/123392
 
2.7%
Other values (40)40
54.1%

Most occurring characters

ValueCountFrequency (%)
t297
 
8.2%
/295
 
8.1%
s164
 
4.5%
e161
 
4.4%
.159
 
4.4%
o153
 
4.2%
h148
 
4.1%
m144
 
4.0%
w137
 
3.8%
c129
 
3.5%
Other values (64)1847
50.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2342
64.4%
Other Punctuation609
 
16.8%
Decimal Number401
 
11.0%
Uppercase Letter188
 
5.2%
Dash Punctuation44
 
1.2%
Connector Punctuation25
 
0.7%
Math Symbol25
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t297
 
12.7%
s164
 
7.0%
e161
 
6.9%
o153
 
6.5%
h148
 
6.3%
m144
 
6.1%
w137
 
5.8%
c129
 
5.5%
p119
 
5.1%
i119
 
5.1%
Other values (16)771
32.9%
Uppercase Letter
ValueCountFrequency (%)
E21
 
11.2%
C14
 
7.4%
B14
 
7.4%
P13
 
6.9%
U12
 
6.4%
D11
 
5.9%
A10
 
5.3%
T9
 
4.8%
M9
 
4.8%
J8
 
4.3%
Other values (15)67
35.6%
Decimal Number
ValueCountFrequency (%)
463
15.7%
354
13.5%
053
13.2%
946
11.5%
145
11.2%
235
8.7%
533
8.2%
826
6.5%
624
 
6.0%
722
 
5.5%
Other Punctuation
ValueCountFrequency (%)
/295
48.4%
.159
26.1%
:74
 
12.2%
%57
 
9.4%
?11
 
1.8%
&8
 
1.3%
,3
 
0.5%
#1
 
0.2%
!1
 
0.2%
Math Symbol
ValueCountFrequency (%)
=23
92.0%
+2
 
8.0%
Dash Punctuation
ValueCountFrequency (%)
-44
100.0%
Connector Punctuation
ValueCountFrequency (%)
_25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2530
69.6%
Common1104
30.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t297
 
11.7%
s164
 
6.5%
e161
 
6.4%
o153
 
6.0%
h148
 
5.8%
m144
 
5.7%
w137
 
5.4%
c129
 
5.1%
p119
 
4.7%
i119
 
4.7%
Other values (41)959
37.9%
Common
ValueCountFrequency (%)
/295
26.7%
.159
14.4%
:74
 
6.7%
463
 
5.7%
%57
 
5.2%
354
 
4.9%
053
 
4.8%
946
 
4.2%
145
 
4.1%
-44
 
4.0%
Other values (13)214
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII3634
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t297
 
8.2%
/295
 
8.1%
s164
 
4.5%
e161
 
4.4%
.159
 
4.4%
o153
 
4.2%
h148
 
4.1%
m144
 
4.0%
w137
 
3.8%
c129
 
3.5%
Other values (64)1847
50.8%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size792.0 B
53 
20:00
15 
10:00
 
4
19:00
 
3
12:00
 
2
Other values (6)

Length

Max length5
Median length0
Mean length1.807228916
Min length0

Characters and Unicode

Total characters150
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)7.2%

Sample

1st row22:00
2nd row12:00
3rd row
4th row
5th row12:00

Common Values

ValueCountFrequency (%)
53
63.9%
20:0015
 
18.1%
10:004
 
4.8%
19:003
 
3.6%
12:002
 
2.4%
22:001
 
1.2%
08:001
 
1.2%
06:001
 
1.2%
20:451
 
1.2%
00:001
 
1.2%

Length

2022-09-05T21:46:33.118140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0015
50.0%
10:004
 
13.3%
19:003
 
10.0%
12:002
 
6.7%
22:001
 
3.3%
08:001
 
3.3%
06:001
 
3.3%
20:451
 
3.3%
00:001
 
3.3%
21:001
 
3.3%

Most occurring characters

ValueCountFrequency (%)
082
54.7%
:30
 
20.0%
221
 
14.0%
110
 
6.7%
93
 
2.0%
81
 
0.7%
61
 
0.7%
41
 
0.7%
51
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number120
80.0%
Other Punctuation30
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
082
68.3%
221
 
17.5%
110
 
8.3%
93
 
2.5%
81
 
0.8%
61
 
0.8%
41
 
0.8%
51
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
082
54.7%
:30
 
20.0%
221
 
14.0%
110
 
6.7%
93
 
2.0%
81
 
0.7%
61
 
0.7%
41
 
0.7%
51
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
082
54.7%
:30
 
20.0%
221
 
14.0%
110
 
6.7%
93
 
2.0%
81
 
0.7%
61
 
0.7%
41
 
0.7%
51
 
0.7%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size792.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5
Distinct (%)83.3%
Missing77
Missing (%)92.8%
Memory size792.0 B
7.2
7.7
7.3
7.6
7.5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters18
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row7.7
2nd row7.3
3rd row7.2
4th row7.2
5th row7.6

Common Values

ValueCountFrequency (%)
7.22
 
2.4%
7.71
 
1.2%
7.31
 
1.2%
7.61
 
1.2%
7.51
 
1.2%
(Missing)77
92.8%

Length

2022-09-05T21:46:33.200373image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:33.289799image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.22
33.3%
7.71
16.7%
7.31
16.7%
7.61
16.7%
7.51
16.7%

Most occurring characters

ValueCountFrequency (%)
77
38.9%
.6
33.3%
22
 
11.1%
31
 
5.6%
61
 
5.6%
51
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12
66.7%
Other Punctuation6
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
77
58.3%
22
 
16.7%
31
 
8.3%
61
 
8.3%
51
 
8.3%
Other Punctuation
ValueCountFrequency (%)
.6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common18
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
77
38.9%
.6
33.3%
22
 
11.1%
31
 
5.6%
61
 
5.6%
51
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
38.9%
.6
33.3%
22
 
11.1%
31
 
5.6%
61
 
5.6%
51
 
5.6%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct40
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.3373494
Minimum1
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:33.381431image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q121
median30
Q335
95-th percentile82.8
Maximum95
Range94
Interquartile range (IQR)14

Descriptive statistics

Standard deviation21.75040067
Coefficient of variation (CV)0.6334327214
Kurtosis0.7958493181
Mean34.3373494
Median Absolute Deviation (MAD)9
Skewness1.192395464
Sum2850
Variance473.0799295
MonotonicityNot monotonic
2022-09-05T21:46:33.491470image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
3416
19.3%
219
 
10.8%
244
 
4.8%
274
 
4.8%
363
 
3.6%
303
 
3.6%
283
 
3.6%
332
 
2.4%
832
 
2.4%
152
 
2.4%
Other values (30)35
42.2%
ValueCountFrequency (%)
11
1.2%
31
1.2%
51
1.2%
71
1.2%
82
2.4%
91
1.2%
121
1.2%
132
2.4%
152
2.4%
162
2.4%
ValueCountFrequency (%)
951
1.2%
881
1.2%
841
1.2%
832
2.4%
811
1.2%
801
1.2%
791
1.2%
751
1.2%
721
1.2%
691
1.2%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing83
Missing (%)100.0%
Memory size792.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct28
Distinct (%)34.6%
Missing2
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean151.308642
Minimum15
Maximum518
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:33.580614image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile21
Q130
median104
Q3262
95-th percentile445
Maximum518
Range503
Interquartile range (IQR)232

Descriptive statistics

Standard deviation146.1842709
Coefficient of variation (CV)0.9661329912
Kurtosis0.1127064971
Mean151.308642
Median Absolute Deviation (MAD)83
Skewness1.095831973
Sum12256
Variance21369.84105
MonotonicityNot monotonic
2022-09-05T21:46:33.681386image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2117
20.5%
6712
14.5%
1048
 
9.6%
2625
 
6.0%
2814
 
4.8%
1184
 
4.8%
303
 
3.6%
323
 
3.6%
152
 
2.4%
5182
 
2.4%
Other values (18)21
25.3%
ValueCountFrequency (%)
152
 
2.4%
2117
20.5%
303
 
3.6%
323
 
3.6%
401
 
1.2%
6712
14.5%
1021
 
1.2%
1048
9.6%
1184
 
4.8%
1221
 
1.2%
ValueCountFrequency (%)
5182
2.4%
5161
1.2%
4931
1.2%
4452
2.4%
4141
1.2%
4131
1.2%
3791
1.2%
3671
1.2%
3371
1.2%
3272
2.4%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct28
Distinct (%)34.6%
Missing2
Missing (%)2.4%
Memory size792.0 B
YouTube
17 
iQIYI
12 
Tencent QQ
myTV SUPER
Premier
Other values (23)
35 

Length

Max length20
Median length13
Mean length7.654320988
Min length3

Characters and Unicode

Total characters620
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)18.5%

Sample

1st rowPremier
2nd rowPremier
3rd rowPremier
4th rowPremier
5th rowivi

Common Values

ValueCountFrequency (%)
YouTube17
20.5%
iQIYI12
14.5%
Tencent QQ8
 
9.6%
myTV SUPER5
 
6.0%
Premier4
 
4.8%
Youku4
 
4.8%
Naver TVCast3
 
3.6%
Rooster Teeth3
 
3.6%
WWE Network2
 
2.4%
Go32
 
2.4%
Other values (18)21
25.3%

Length

2022-09-05T21:46:33.776605image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube17
 
14.5%
iqiyi12
 
10.3%
tv8
 
6.8%
tencent8
 
6.8%
qq8
 
6.8%
mytv5
 
4.3%
super5
 
4.3%
premier4
 
3.4%
youku4
 
3.4%
naver3
 
2.6%
Other values (29)43
36.8%

Most occurring characters

ValueCountFrequency (%)
e64
 
10.3%
T49
 
7.9%
u45
 
7.3%
o40
 
6.5%
36
 
5.8%
Y33
 
5.3%
Q28
 
4.5%
I27
 
4.4%
t24
 
3.9%
i23
 
3.7%
Other values (35)251
40.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter348
56.1%
Uppercase Letter231
37.3%
Space Separator36
 
5.8%
Decimal Number4
 
0.6%
Math Symbol1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e64
18.4%
u45
12.9%
o40
11.5%
t24
 
6.9%
i23
 
6.6%
r20
 
5.7%
n19
 
5.5%
b18
 
5.2%
a16
 
4.6%
c12
 
3.4%
Other values (11)67
19.3%
Uppercase Letter
ValueCountFrequency (%)
T49
21.2%
Y33
14.3%
Q28
12.1%
I27
11.7%
V19
 
8.2%
P14
 
6.1%
R9
 
3.9%
W8
 
3.5%
N8
 
3.5%
E8
 
3.5%
Other values (10)28
12.1%
Decimal Number
ValueCountFrequency (%)
22
50.0%
32
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Math Symbol
ValueCountFrequency (%)
+1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin579
93.4%
Common41
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e64
 
11.1%
T49
 
8.5%
u45
 
7.8%
o40
 
6.9%
Y33
 
5.7%
Q28
 
4.8%
I27
 
4.7%
t24
 
4.1%
i23
 
4.0%
r20
 
3.5%
Other values (31)226
39.0%
Common
ValueCountFrequency (%)
36
87.8%
22
 
4.9%
32
 
4.9%
+1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e64
 
10.3%
T49
 
7.9%
u45
 
7.3%
o40
 
6.5%
36
 
5.8%
Y33
 
5.3%
Q28
 
4.5%
I27
 
4.4%
t24
 
3.9%
i23
 
3.7%
Other values (35)251
40.5%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)22.7%
Missing39
Missing (%)47.0%
Memory size792.0 B
China
15 
United States
Russian Federation
Hong Kong
Korea, Republic of
Other values (5)

Length

Max length25
Median length18
Mean length10.40909091
Min length5

Characters and Unicode

Total characters458
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.8%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowRussian Federation
5th rowRussian Federation

Common Values

ValueCountFrequency (%)
China15
 
18.1%
United States7
 
8.4%
Russian Federation5
 
6.0%
Hong Kong5
 
6.0%
Korea, Republic of4
 
4.8%
Norway3
 
3.6%
Taiwan, Province of China2
 
2.4%
Japan1
 
1.2%
Poland1
 
1.2%
Turkey1
 
1.2%
(Missing)39
47.0%

Length

2022-09-05T21:46:33.876648image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:33.992842image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
china17
22.7%
united7
9.3%
states7
9.3%
of6
 
8.0%
russian5
 
6.7%
federation5
 
6.7%
hong5
 
6.7%
kong5
 
6.7%
korea4
 
5.3%
republic4
 
5.3%
Other values (6)10
13.3%

Most occurring characters

ValueCountFrequency (%)
n50
 
10.9%
a48
 
10.5%
i42
 
9.2%
e35
 
7.6%
31
 
6.8%
o31
 
6.8%
t26
 
5.7%
C17
 
3.7%
h17
 
3.7%
s17
 
3.7%
Other values (24)144
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter352
76.9%
Uppercase Letter69
 
15.1%
Space Separator31
 
6.8%
Other Punctuation6
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n50
14.2%
a48
13.6%
i42
11.9%
e35
9.9%
o31
8.8%
t26
7.4%
h17
 
4.8%
s17
 
4.8%
r15
 
4.3%
d13
 
3.7%
Other values (11)58
16.5%
Uppercase Letter
ValueCountFrequency (%)
C17
24.6%
R9
13.0%
K9
13.0%
S7
10.1%
U7
10.1%
H5
 
7.2%
F5
 
7.2%
N3
 
4.3%
T3
 
4.3%
P3
 
4.3%
Space Separator
ValueCountFrequency (%)
31
100.0%
Other Punctuation
ValueCountFrequency (%)
,6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin421
91.9%
Common37
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n50
11.9%
a48
 
11.4%
i42
 
10.0%
e35
 
8.3%
o31
 
7.4%
t26
 
6.2%
C17
 
4.0%
h17
 
4.0%
s17
 
4.0%
r15
 
3.6%
Other values (22)123
29.2%
Common
ValueCountFrequency (%)
31
83.8%
,6
 
16.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n50
 
10.9%
a48
 
10.5%
i42
 
9.2%
e35
 
7.6%
31
 
6.8%
o31
 
6.8%
t26
 
5.7%
C17
 
3.7%
h17
 
3.7%
s17
 
3.7%
Other values (24)144
31.4%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)22.7%
Missing39
Missing (%)47.0%
Memory size792.0 B
CN
15 
US
RU
HK
KR
Other values (5)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters88
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.8%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowRU
5th rowRU

Common Values

ValueCountFrequency (%)
CN15
 
18.1%
US7
 
8.4%
RU5
 
6.0%
HK5
 
6.0%
KR4
 
4.8%
NO3
 
3.6%
TW2
 
2.4%
JP1
 
1.2%
PL1
 
1.2%
TR1
 
1.2%
(Missing)39
47.0%

Length

2022-09-05T21:46:34.083194image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:34.186717image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cn15
34.1%
us7
15.9%
ru5
 
11.4%
hk5
 
11.4%
kr4
 
9.1%
no3
 
6.8%
tw2
 
4.5%
jp1
 
2.3%
pl1
 
2.3%
tr1
 
2.3%

Most occurring characters

ValueCountFrequency (%)
N18
20.5%
C15
17.0%
U12
13.6%
R10
11.4%
K9
10.2%
S7
 
8.0%
H5
 
5.7%
O3
 
3.4%
T3
 
3.4%
W2
 
2.3%
Other values (3)4
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter88
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N18
20.5%
C15
17.0%
U12
13.6%
R10
11.4%
K9
10.2%
S7
 
8.0%
H5
 
5.7%
O3
 
3.4%
T3
 
3.4%
W2
 
2.3%
Other values (3)4
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Latin88
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N18
20.5%
C15
17.0%
U12
13.6%
R10
11.4%
K9
10.2%
S7
 
8.0%
H5
 
5.7%
O3
 
3.4%
T3
 
3.4%
W2
 
2.3%
Other values (3)4
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII88
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N18
20.5%
C15
17.0%
U12
13.6%
R10
11.4%
K9
10.2%
S7
 
8.0%
H5
 
5.7%
O3
 
3.4%
T3
 
3.4%
W2
 
2.3%
Other values (3)4
 
4.5%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)22.7%
Missing39
Missing (%)47.0%
Memory size792.0 B
Asia/Shanghai
15 
America/New_York
Asia/Kamchatka
Asia/Hong_Kong
Asia/Seoul
Other values (5)

Length

Max length16
Median length15
Mean length13.18181818
Min length10

Characters and Unicode

Total characters580
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.8%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Kamchatka
5th rowAsia/Kamchatka

Common Values

ValueCountFrequency (%)
Asia/Shanghai15
 
18.1%
America/New_York7
 
8.4%
Asia/Kamchatka5
 
6.0%
Asia/Hong_Kong5
 
6.0%
Asia/Seoul4
 
4.8%
Europe/Oslo3
 
3.6%
Asia/Taipei2
 
2.4%
Asia/Tokyo1
 
1.2%
Europe/Warsaw1
 
1.2%
Europe/Istanbul1
 
1.2%
(Missing)39
47.0%

Length

2022-09-05T21:46:34.286722image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:34.398445image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai15
34.1%
america/new_york7
15.9%
asia/kamchatka5
 
11.4%
asia/hong_kong5
 
11.4%
asia/seoul4
 
9.1%
europe/oslo3
 
6.8%
asia/taipei2
 
4.5%
asia/tokyo1
 
2.3%
europe/warsaw1
 
2.3%
europe/istanbul1
 
2.3%

Most occurring characters

ValueCountFrequency (%)
a89
15.3%
i58
 
10.0%
/44
 
7.6%
A39
 
6.7%
s37
 
6.4%
h35
 
6.0%
o31
 
5.3%
n26
 
4.5%
e25
 
4.3%
g25
 
4.3%
Other values (22)171
29.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter424
73.1%
Uppercase Letter100
 
17.2%
Other Punctuation44
 
7.6%
Connector Punctuation12
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a89
21.0%
i58
13.7%
s37
8.7%
h35
 
8.3%
o31
 
7.3%
n26
 
6.1%
e25
 
5.9%
g25
 
5.9%
r20
 
4.7%
k13
 
3.1%
Other values (9)65
15.3%
Uppercase Letter
ValueCountFrequency (%)
A39
39.0%
S19
19.0%
K10
 
10.0%
Y7
 
7.0%
N7
 
7.0%
H5
 
5.0%
E5
 
5.0%
O3
 
3.0%
T3
 
3.0%
W1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/44
100.0%
Connector Punctuation
ValueCountFrequency (%)
_12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin524
90.3%
Common56
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a89
17.0%
i58
11.1%
A39
 
7.4%
s37
 
7.1%
h35
 
6.7%
o31
 
5.9%
n26
 
5.0%
e25
 
4.8%
g25
 
4.8%
r20
 
3.8%
Other values (20)139
26.5%
Common
ValueCountFrequency (%)
/44
78.6%
_12
 
21.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a89
15.3%
i58
 
10.0%
/44
 
7.6%
A39
 
6.7%
s37
 
6.4%
h35
 
6.0%
o31
 
5.3%
n26
 
4.5%
e25
 
4.3%
g25
 
4.3%
Other values (22)171
29.5%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)19.6%
Missing37
Missing (%)44.6%
Memory size792.0 B
https://www.youtube.com
17 
https://www.iq.com/
12 
https://v.qq.com/
https://tv.naver.com/
https://w.mgtv.com/
Other values (4)

Length

Max length30
Median length25
Mean length20.58695652
Min length17

Characters and Unicode

Total characters947
Distinct characters24
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)8.7%

Sample

1st rowhttps://www.ivi.ru/
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://v.qq.com/
5th rowhttps://www.vlive.tv/home

Common Values

ValueCountFrequency (%)
https://www.youtube.com17
20.5%
https://www.iq.com/12
 
14.5%
https://v.qq.com/8
 
9.6%
https://tv.naver.com/3
 
3.6%
https://w.mgtv.com/2
 
2.4%
https://www.ivi.ru/1
 
1.2%
https://www.vlive.tv/home1
 
1.2%
https://wetv.vip/1
 
1.2%
https://www.discoveryplus.com/1
 
1.2%
(Missing)37
44.6%

Length

2022-09-05T21:46:34.497921image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:34.596378image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.youtube.com17
37.0%
https://www.iq.com12
26.1%
https://v.qq.com8
17.4%
https://tv.naver.com3
 
6.5%
https://w.mgtv.com2
 
4.3%
https://www.ivi.ru1
 
2.2%
https://www.vlive.tv/home1
 
2.2%
https://wetv.vip1
 
2.2%
https://www.discoveryplus.com1
 
2.2%

Most occurring characters

ValueCountFrequency (%)
/121
12.8%
t116
12.2%
w99
10.5%
.91
9.6%
o62
 
6.5%
p48
 
5.1%
s48
 
5.1%
h47
 
5.0%
:46
 
4.9%
m46
 
4.9%
Other values (14)223
23.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter689
72.8%
Other Punctuation258
 
27.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t116
16.8%
w99
14.4%
o62
9.0%
p48
7.0%
s48
7.0%
h47
6.8%
m46
 
6.7%
c44
 
6.4%
u36
 
5.2%
q28
 
4.1%
Other values (11)115
16.7%
Other Punctuation
ValueCountFrequency (%)
/121
46.9%
.91
35.3%
:46
 
17.8%

Most occurring scripts

ValueCountFrequency (%)
Latin689
72.8%
Common258
 
27.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t116
16.8%
w99
14.4%
o62
9.0%
p48
7.0%
s48
7.0%
h47
6.8%
m46
 
6.7%
c44
 
6.4%
u36
 
5.2%
q28
 
4.1%
Other values (11)115
16.7%
Common
ValueCountFrequency (%)
/121
46.9%
.91
35.3%
:46
 
17.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII947
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/121
12.8%
t116
12.2%
w99
10.5%
.91
9.6%
o62
 
6.5%
p48
 
5.1%
s48
 
5.1%
h47
 
5.0%
:46
 
4.9%
m46
 
4.9%
Other values (14)223
23.5%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing83
Missing (%)100.0%
Memory size792.0 B

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing80
Missing (%)96.4%
Memory size792.0 B
30282.0
19056.0
6659.0

Length

Max length7
Median length7
Mean length6.666666667
Min length6

Characters and Unicode

Total characters20
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row30282.0
2nd row19056.0
3rd row6659.0

Common Values

ValueCountFrequency (%)
30282.01
 
1.2%
19056.01
 
1.2%
6659.01
 
1.2%
(Missing)80
96.4%

Length

2022-09-05T21:46:34.690930image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:34.776247image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
30282.01
33.3%
19056.01
33.3%
6659.01
33.3%

Most occurring characters

ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number17
85.0%
Other Punctuation3
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
05
29.4%
63
17.6%
22
 
11.8%
92
 
11.8%
52
 
11.8%
31
 
5.9%
81
 
5.9%
11
 
5.9%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct44
Distinct (%)75.9%
Missing25
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean337155.7759
Minimum73246
Maximum410187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:34.863790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum73246
5-th percentile100464.75
Q1312683.5
median381485
Q3393662.75
95-th percentile402864.9
Maximum410187
Range336941
Interquartile range (IQR)80979.25

Descriptive statistics

Standard deviation88389.10858
Coefficient of variation (CV)0.2621610392
Kurtosis2.838879142
Mean337155.7759
Median Absolute Deviation (MAD)15762
Skewness-1.846292396
Sum19555035
Variance7812634516
MonotonicityNot monotonic
2022-09-05T21:46:34.981875image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
3934735
 
6.0%
3944673
 
3.6%
3922142
 
2.4%
3972472
 
2.4%
3933812
 
2.4%
2608292
 
2.4%
2787932
 
2.4%
3937262
 
2.4%
4101872
 
2.4%
3940872
 
2.4%
Other values (34)34
41.0%
(Missing)25
30.1%
ValueCountFrequency (%)
732461
1.2%
767791
1.2%
788961
1.2%
1042711
1.2%
1449911
1.2%
2479561
1.2%
2608292
2.4%
2644581
1.2%
2651931
1.2%
2658651
1.2%
ValueCountFrequency (%)
4101872
 
2.4%
4089561
 
1.2%
4017901
 
1.2%
3972472
 
2.4%
3946271
 
1.2%
3944673
3.6%
3940872
 
2.4%
3940451
 
1.2%
3937262
 
2.4%
3934735
6.0%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct23
Distinct (%)88.5%
Missing57
Missing (%)68.7%
Memory size792.0 B
tt13598988
tt14125832
tt1714810
tt13370842
 
1
tt0185103
 
1
Other values (18)
18 

Length

Max length10
Median length9
Mean length9.423076923
Min length9

Characters and Unicode

Total characters245
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)76.9%

Sample

1st rowtt8561620
2nd rowtt14125832
3rd rowtt14125832
4th rowtt12923874
5th rowtt11492320

Common Values

ValueCountFrequency (%)
tt135989882
 
2.4%
tt141258322
 
2.4%
tt17148102
 
2.4%
tt133708421
 
1.2%
tt01851031
 
1.2%
tt47931901
 
1.2%
tt00965971
 
1.2%
tt18682071
 
1.2%
tt35416561
 
1.2%
tt74319941
 
1.2%
Other values (13)13
 
15.7%
(Missing)57
68.7%

Length

2022-09-05T21:46:41.727493image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt135989882
 
7.7%
tt17148102
 
7.7%
tt141258322
 
7.7%
tt92067881
 
3.8%
tt129238741
 
3.8%
tt114923201
 
3.8%
tt107270441
 
3.8%
tt04017471
 
3.8%
tt03375341
 
3.8%
tt40870321
 
3.8%
Other values (13)13
50.0%

Most occurring characters

ValueCountFrequency (%)
t52
21.2%
130
12.2%
827
11.0%
320
 
8.2%
420
 
8.2%
220
 
8.2%
019
 
7.8%
917
 
6.9%
717
 
6.9%
612
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number193
78.8%
Lowercase Letter52
 
21.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
130
15.5%
827
14.0%
320
10.4%
420
10.4%
220
10.4%
019
9.8%
917
8.8%
717
8.8%
612
 
6.2%
511
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
t52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common193
78.8%
Latin52
 
21.2%

Most frequent character per script

Common
ValueCountFrequency (%)
130
15.5%
827
14.0%
320
10.4%
420
10.4%
220
10.4%
019
9.8%
917
8.8%
717
8.8%
612
 
6.2%
511
 
5.7%
Latin
ValueCountFrequency (%)
t52
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII245
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t52
21.2%
130
12.2%
827
11.0%
320
 
8.2%
420
 
8.2%
220
 
8.2%
019
 
7.8%
917
 
6.9%
717
 
6.9%
612
 
4.9%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct54
Distinct (%)66.7%
Missing2
Missing (%)2.4%
Memory size792.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg
12 
https://static.tvmaze.com/uploads/images/medium_portrait/289/723058.jpg
 
5
https://static.tvmaze.com/uploads/images/medium_portrait/320/800829.jpg
 
3
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg
 
2
Other values (49)
57 

Length

Max length72
Median length71
Mean length70.87654321
Min length69

Characters and Unicode

Total characters5741
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)50.6%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/289/722910.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/285/713049.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/289/723328.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg12
 
14.5%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723058.jpg5
 
6.0%
https://static.tvmaze.com/uploads/images/medium_portrait/320/800829.jpg3
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/23/59540.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729461.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/medium_portrait/292/731348.jpg2
 
2.4%
Other values (44)47
56.6%

Length

2022-09-05T21:46:41.815038image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/290/727385.jpg12
 
14.8%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723058.jpg5
 
6.2%
https://static.tvmaze.com/uploads/images/medium_portrait/320/800829.jpg3
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/414/1035476.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/292/731348.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729461.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/23/59540.jpg2
 
2.5%
Other values (44)47
58.0%

Most occurring characters

ValueCountFrequency (%)
t567
 
9.9%
/567
 
9.9%
m405
 
7.1%
a405
 
7.1%
p324
 
5.6%
s324
 
5.6%
i324
 
5.6%
o243
 
4.2%
.243
 
4.2%
e243
 
4.2%
Other values (22)2096
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4050
70.5%
Other Punctuation891
 
15.5%
Decimal Number719
 
12.5%
Connector Punctuation81
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t567
14.0%
m405
10.0%
a405
10.0%
p324
 
8.0%
s324
 
8.0%
i324
 
8.0%
o243
 
6.0%
e243
 
6.0%
u162
 
4.0%
c162
 
4.0%
Other values (8)891
22.0%
Decimal Number
ValueCountFrequency (%)
2110
15.3%
793
12.9%
883
11.5%
373
10.2%
072
10.0%
970
9.7%
564
8.9%
164
8.9%
451
7.1%
639
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/567
63.6%
.243
27.3%
:81
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4050
70.5%
Common1691
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t567
14.0%
m405
10.0%
a405
10.0%
p324
 
8.0%
s324
 
8.0%
i324
 
8.0%
o243
 
6.0%
e243
 
6.0%
u162
 
4.0%
c162
 
4.0%
Other values (8)891
22.0%
Common
ValueCountFrequency (%)
/567
33.5%
.243
14.4%
2110
 
6.5%
793
 
5.5%
883
 
4.9%
_81
 
4.8%
:81
 
4.8%
373
 
4.3%
072
 
4.3%
970
 
4.1%
Other values (4)218
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII5741
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t567
 
9.9%
/567
 
9.9%
m405
 
7.1%
a405
 
7.1%
p324
 
5.6%
s324
 
5.6%
i324
 
5.6%
o243
 
4.2%
.243
 
4.2%
e243
 
4.2%
Other values (22)2096
36.5%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct54
Distinct (%)66.7%
Missing2
Missing (%)2.4%
Memory size792.0 B
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg
12 
https://static.tvmaze.com/uploads/images/original_untouched/289/723058.jpg
 
5
https://static.tvmaze.com/uploads/images/original_untouched/320/800829.jpg
 
3
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg
 
2
Other values (49)
57 

Length

Max length75
Median length74
Mean length73.87654321
Min length72

Characters and Unicode

Total characters5984
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)50.6%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/289/722910.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/713049.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/289/723328.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg12
 
14.5%
https://static.tvmaze.com/uploads/images/original_untouched/289/723058.jpg5
 
6.0%
https://static.tvmaze.com/uploads/images/original_untouched/320/800829.jpg3
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/23/59540.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/291/729461.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
2.4%
https://static.tvmaze.com/uploads/images/original_untouched/292/731348.jpg2
 
2.4%
Other values (44)47
56.6%

Length

2022-09-05T21:46:41.908833image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/727385.jpg12
 
14.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/723058.jpg5
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/320/800829.jpg3
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/414/1035476.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/292/731348.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/291/729461.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/23/59540.jpg2
 
2.5%
Other values (44)47
58.0%

Most occurring characters

ValueCountFrequency (%)
/567
 
9.5%
t486
 
8.1%
a405
 
6.8%
s324
 
5.4%
i324
 
5.4%
o324
 
5.4%
p243
 
4.1%
c243
 
4.1%
.243
 
4.1%
g243
 
4.1%
Other values (23)2582
43.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4293
71.7%
Other Punctuation891
 
14.9%
Decimal Number719
 
12.0%
Connector Punctuation81
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t486
 
11.3%
a405
 
9.4%
s324
 
7.5%
i324
 
7.5%
o324
 
7.5%
p243
 
5.7%
c243
 
5.7%
g243
 
5.7%
m243
 
5.7%
e243
 
5.7%
Other values (9)1215
28.3%
Decimal Number
ValueCountFrequency (%)
2110
15.3%
793
12.9%
883
11.5%
373
10.2%
072
10.0%
970
9.7%
564
8.9%
164
8.9%
451
7.1%
639
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/567
63.6%
.243
27.3%
:81
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4293
71.7%
Common1691
 
28.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t486
 
11.3%
a405
 
9.4%
s324
 
7.5%
i324
 
7.5%
o324
 
7.5%
p243
 
5.7%
c243
 
5.7%
g243
 
5.7%
m243
 
5.7%
e243
 
5.7%
Other values (9)1215
28.3%
Common
ValueCountFrequency (%)
/567
33.5%
.243
14.4%
2110
 
6.5%
793
 
5.5%
883
 
4.9%
:81
 
4.8%
_81
 
4.8%
373
 
4.3%
072
 
4.3%
970
 
4.1%
Other values (4)218
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII5984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/567
 
9.5%
t486
 
8.1%
a405
 
6.8%
s324
 
5.4%
i324
 
5.4%
o324
 
5.4%
p243
 
4.1%
c243
 
4.1%
.243
 
4.1%
g243
 
4.1%
Other values (23)2582
43.1%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING

Distinct50
Distinct (%)69.4%
Missing11
Missing (%)13.3%
Memory size792.0 B
<p>The play is set in the turbulent period of the Republic of China in Shanghai. In a turbulent era, the forensic doctor Che Suwei and the gentleman detective Gu Yuan are intertwined with various forces. "Deputy Inspector Kang Yichen, and the innocent and lively reporter Cao Qingluo worked together to crack out a number of weird and curious cases, and restore the truth.</p>
12 
<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>
 
3
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>
 
2
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>
 
2
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>
 
2
Other values (45)
51 

Length

Max length913
Median length553
Mean length365.1527778
Min length58

Characters and Unicode

Total characters26291
Distinct characters95
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)54.2%

Sample

1st row<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>
2nd row<p>This is not an interview, this is a confession. Revelations of the artist in the form of a monologue. The guest's opinion may not coincide with the opinion of the PREMIER platform editorial board.</p>
3rd row<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>
4th row<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>
5th row<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>

Common Values

ValueCountFrequency (%)
<p>The play is set in the turbulent period of the Republic of China in Shanghai. In a turbulent era, the forensic doctor Che Suwei and the gentleman detective Gu Yuan are intertwined with various forces. "Deputy Inspector Kang Yichen, and the innocent and lively reporter Cao Qingluo worked together to crack out a number of weird and curious cases, and restore the truth.</p>12
 
14.5%
<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>3
 
3.6%
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>2
 
2.4%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>2
 
2.4%
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>2
 
2.4%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.4%
<p>The series is a fantasy comic web drama that tells a story of three students, who were studying in Seowon during the Joseon period accidently time travel and arrive at present-day Seowon in 2020.</p>2
 
2.4%
<p>The disciples of the Lingchuan Sect have guarded the Fans of Heaven and Earth for nearly a century. Mu Yun and Hua Yue are the only disciples of the sect that are left. The stubborn and disobedient Hua Yue unintentionally discovers that the Fan of Heaven possesses the power to travel through time. To escape being forced to study and practice martial arts by Mu Yun, Hua Yue travels to the future to have fun. Hundreds of years in the future she meets Xiao Qian who looks exactly like her. Secrets come to the surface, and adventures take place.</p>2
 
2.4%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
2.4%
<p>Ju Xuanwen (Wan Yan Lo-yun) is a man with a noble appearance and many virtues. It is a pity that he fell ill with neurosis at a young age - after an unexplained car accident he falls into a delusional state and considers himself a prince. Since then, he no longer cares about the activities of his company and concentrates on becoming emperor.<br />Lo Huai (Chuang Da Fei) - psychiatrist on the verge of bankruptcy. Because of the need for money, she took responsibility for the treatment of Ju Xuanwen. However, she did not expect her peaceful days to end one day. Spending time together, they began to fall in love with each other.</p>2
 
2.4%
Other values (40)41
49.4%
(Missing)11
 
13.3%

Length

2022-09-05T21:46:42.023559image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the315
 
7.1%
and173
 
3.9%
of161
 
3.6%
a129
 
2.9%
in128
 
2.9%
to124
 
2.8%
with52
 
1.2%
is49
 
1.1%
that37
 
0.8%
are28
 
0.6%
Other values (1298)3234
73.0%

Most occurring characters

ValueCountFrequency (%)
4348
16.5%
e2563
 
9.7%
t1836
 
7.0%
a1637
 
6.2%
n1603
 
6.1%
o1515
 
5.8%
i1367
 
5.2%
r1313
 
5.0%
s1119
 
4.3%
h1058
 
4.0%
Other values (85)7932
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter19847
75.5%
Space Separator4358
 
16.6%
Uppercase Letter893
 
3.4%
Other Punctuation661
 
2.5%
Math Symbol400
 
1.5%
Decimal Number70
 
0.3%
Dash Punctuation41
 
0.2%
Open Punctuation10
 
< 0.1%
Close Punctuation10
 
< 0.1%
Currency Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2563
12.9%
t1836
 
9.3%
a1637
 
8.2%
n1603
 
8.1%
o1515
 
7.6%
i1367
 
6.9%
r1313
 
6.6%
s1119
 
5.6%
h1058
 
5.3%
d748
 
3.8%
Other values (30)5088
25.6%
Uppercase Letter
ValueCountFrequency (%)
S90
 
10.1%
T80
 
9.0%
Y77
 
8.6%
C55
 
6.2%
R48
 
5.4%
I45
 
5.0%
W42
 
4.7%
A42
 
4.7%
D37
 
4.1%
M37
 
4.1%
Other values (17)340
38.1%
Other Punctuation
ValueCountFrequency (%)
,244
36.9%
.213
32.2%
/103
15.6%
"42
 
6.4%
'38
 
5.7%
:10
 
1.5%
!7
 
1.1%
?2
 
0.3%
&1
 
0.2%
;1
 
0.2%
Decimal Number
ValueCountFrequency (%)
020
28.6%
217
24.3%
110
14.3%
97
 
10.0%
35
 
7.1%
84
 
5.7%
53
 
4.3%
62
 
2.9%
72
 
2.9%
Space Separator
ValueCountFrequency (%)
4348
99.8%
 10
 
0.2%
Math Symbol
ValueCountFrequency (%)
>200
50.0%
<200
50.0%
Dash Punctuation
ValueCountFrequency (%)
-33
80.5%
8
 
19.5%
Open Punctuation
ValueCountFrequency (%)
(10
100.0%
Close Punctuation
ValueCountFrequency (%)
)10
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin20729
78.8%
Common5551
 
21.1%
Cyrillic11
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2563
12.4%
t1836
 
8.9%
a1637
 
7.9%
n1603
 
7.7%
o1515
 
7.3%
i1367
 
6.6%
r1313
 
6.3%
s1119
 
5.4%
h1058
 
5.1%
d748
 
3.6%
Other values (47)5970
28.8%
Common
ValueCountFrequency (%)
4348
78.3%
,244
 
4.4%
.213
 
3.8%
>200
 
3.6%
<200
 
3.6%
/103
 
1.9%
"42
 
0.8%
'38
 
0.7%
-33
 
0.6%
020
 
0.4%
Other values (18)110
 
2.0%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
я1
9.1%
м1
9.1%
е1
9.1%
т1
9.1%
к1
9.1%
с1
9.1%
ж1
9.1%
у1
9.1%
М1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII26257
99.9%
None15
 
0.1%
Cyrillic11
 
< 0.1%
Punctuation8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4348
16.6%
e2563
 
9.8%
t1836
 
7.0%
a1637
 
6.2%
n1603
 
6.1%
o1515
 
5.8%
i1367
 
5.2%
r1313
 
5.0%
s1119
 
4.3%
h1058
 
4.0%
Other values (68)7898
30.1%
None
ValueCountFrequency (%)
 10
66.7%
å1
 
6.7%
ç1
 
6.7%
ı1
 
6.7%
ā1
 
6.7%
é1
 
6.7%
Punctuation
ValueCountFrequency (%)
8
100.0%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
я1
9.1%
м1
9.1%
е1
9.1%
т1
9.1%
к1
9.1%
с1
9.1%
ж1
9.1%
у1
9.1%
М1
9.1%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct56
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1642193156
Minimum1609060726
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size792.0 B
2022-09-05T21:46:42.134190image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1609060726
5-th percentile1610243441
Q11627341874
median1648190058
Q31655666546
95-th percentile1661605405
Maximum1662346277
Range53285551
Interquartile range (IQR)28324673

Descriptive statistics

Standard deviation18720512.68
Coefficient of variation (CV)0.01139970205
Kurtosis-0.9887256769
Mean1642193156
Median Absolute Deviation (MAD)10341752
Skewness-0.7473305771
Sum1.363020319 × 1011
Variance3.50457595 × 1014
MonotonicityNot monotonic
2022-09-05T21:46:42.257840image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165497608612
 
14.5%
16115389485
 
6.0%
16426893193
 
3.6%
16404355312
 
2.4%
16090607262
 
2.4%
16095351412
 
2.4%
16563570072
 
2.4%
16499562022
 
2.4%
16124781452
 
2.4%
16184666822
 
2.4%
Other values (46)49
59.0%
ValueCountFrequency (%)
16090607262
 
2.4%
16095351412
 
2.4%
16101108411
 
1.2%
16114368421
 
1.2%
16115389485
6.0%
16117257131
 
1.2%
16124781452
 
2.4%
16130883481
 
1.2%
16133564461
 
1.2%
16154510692
 
2.4%
ValueCountFrequency (%)
16623462771
1.2%
16621306411
1.2%
16620480541
1.2%
16620301001
1.2%
16616322671
1.2%
16613636441
1.2%
16613587702
2.4%
16613542561
1.2%
16613364421
1.2%
16610060421
1.2%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct56
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Memory size792.0 B
https://api.tvmaze.com/shows/52655
12 
https://api.tvmaze.com/shows/52479
 
5
https://api.tvmaze.com/shows/54541
 
3
https://api.tvmaze.com/shows/52181
 
2
https://api.tvmaze.com/shows/52159
 
2
Other values (51)
59 

Length

Max length34
Median length34
Mean length33.89156627
Min length32

Characters and Unicode

Total characters2813
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)51.8%

Sample

1st rowhttps://api.tvmaze.com/shows/39115
2nd rowhttps://api.tvmaze.com/shows/48683
3rd rowhttps://api.tvmaze.com/shows/52181
4th rowhttps://api.tvmaze.com/shows/52181
5th rowhttps://api.tvmaze.com/shows/52520

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/5265512
 
14.5%
https://api.tvmaze.com/shows/524795
 
6.0%
https://api.tvmaze.com/shows/545413
 
3.6%
https://api.tvmaze.com/shows/521812
 
2.4%
https://api.tvmaze.com/shows/521592
 
2.4%
https://api.tvmaze.com/shows/521042
 
2.4%
https://api.tvmaze.com/shows/627642
 
2.4%
https://api.tvmaze.com/shows/528982
 
2.4%
https://api.tvmaze.com/shows/525242
 
2.4%
https://api.tvmaze.com/shows/547622
 
2.4%
Other values (46)49
59.0%

Length

2022-09-05T21:46:42.362749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/5265512
 
14.5%
https://api.tvmaze.com/shows/524795
 
6.0%
https://api.tvmaze.com/shows/545413
 
3.6%
https://api.tvmaze.com/shows/525242
 
2.4%
https://api.tvmaze.com/shows/152502
 
2.4%
https://api.tvmaze.com/shows/527812
 
2.4%
https://api.tvmaze.com/shows/547622
 
2.4%
https://api.tvmaze.com/shows/61472
 
2.4%
https://api.tvmaze.com/shows/528982
 
2.4%
https://api.tvmaze.com/shows/627642
 
2.4%
Other values (46)49
59.0%

Most occurring characters

ValueCountFrequency (%)
/332
 
11.8%
s249
 
8.9%
t249
 
8.9%
h166
 
5.9%
p166
 
5.9%
a166
 
5.9%
.166
 
5.9%
o166
 
5.9%
m166
 
5.9%
5104
 
3.7%
Other values (16)883
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1826
64.9%
Other Punctuation581
 
20.7%
Decimal Number406
 
14.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s249
13.6%
t249
13.6%
h166
9.1%
p166
9.1%
a166
9.1%
o166
9.1%
m166
9.1%
e83
 
4.5%
w83
 
4.5%
c83
 
4.5%
Other values (3)249
13.6%
Decimal Number
ValueCountFrequency (%)
5104
25.6%
257
14.0%
450
12.3%
645
11.1%
142
10.3%
727
 
6.7%
924
 
5.9%
824
 
5.9%
021
 
5.2%
312
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/332
57.1%
.166
28.6%
:83
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1826
64.9%
Common987
35.1%

Most frequent character per script

Common
ValueCountFrequency (%)
/332
33.6%
.166
16.8%
5104
 
10.5%
:83
 
8.4%
257
 
5.8%
450
 
5.1%
645
 
4.6%
142
 
4.3%
727
 
2.7%
924
 
2.4%
Other values (3)57
 
5.8%
Latin
ValueCountFrequency (%)
s249
13.6%
t249
13.6%
h166
9.1%
p166
9.1%
a166
9.1%
o166
9.1%
m166
9.1%
e83
 
4.5%
w83
 
4.5%
c83
 
4.5%
Other values (3)249
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2813
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/332
 
11.8%
s249
 
8.9%
t249
 
8.9%
h166
 
5.9%
p166
 
5.9%
a166
 
5.9%
.166
 
5.9%
o166
 
5.9%
m166
 
5.9%
5104
 
3.7%
Other values (16)883
31.4%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct56
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Memory size792.0 B
https://api.tvmaze.com/episodes/2340036
12 
https://api.tvmaze.com/episodes/1987350
 
5
https://api.tvmaze.com/episodes/2261133
 
3
https://api.tvmaze.com/episodes/1982412
 
2
https://api.tvmaze.com/episodes/1977651
 
2
Other values (51)
59 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3237
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)51.8%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977905
2nd rowhttps://api.tvmaze.com/episodes/2383519
3rd rowhttps://api.tvmaze.com/episodes/1982412
4th rowhttps://api.tvmaze.com/episodes/1982412
5th rowhttps://api.tvmaze.com/episodes/1988016

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/234003612
 
14.5%
https://api.tvmaze.com/episodes/19873505
 
6.0%
https://api.tvmaze.com/episodes/22611333
 
3.6%
https://api.tvmaze.com/episodes/19824122
 
2.4%
https://api.tvmaze.com/episodes/19776512
 
2.4%
https://api.tvmaze.com/episodes/19760542
 
2.4%
https://api.tvmaze.com/episodes/23539192
 
2.4%
https://api.tvmaze.com/episodes/20057622
 
2.4%
https://api.tvmaze.com/episodes/19880792
 
2.4%
https://api.tvmaze.com/episodes/20714942
 
2.4%
Other values (46)49
59.0%

Length

2022-09-05T21:46:42.453026image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/234003612
 
14.5%
https://api.tvmaze.com/episodes/19873505
 
6.0%
https://api.tvmaze.com/episodes/22611333
 
3.6%
https://api.tvmaze.com/episodes/19880792
 
2.4%
https://api.tvmaze.com/episodes/23012762
 
2.4%
https://api.tvmaze.com/episodes/19985642
 
2.4%
https://api.tvmaze.com/episodes/20714942
 
2.4%
https://api.tvmaze.com/episodes/23790122
 
2.4%
https://api.tvmaze.com/episodes/20057622
 
2.4%
https://api.tvmaze.com/episodes/23539192
 
2.4%
Other values (46)49
59.0%

Most occurring characters

ValueCountFrequency (%)
/332
 
10.3%
p249
 
7.7%
s249
 
7.7%
e249
 
7.7%
t249
 
7.7%
o166
 
5.1%
a166
 
5.1%
i166
 
5.1%
.166
 
5.1%
m166
 
5.1%
Other values (16)1079
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2075
64.1%
Other Punctuation581
 
17.9%
Decimal Number581
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p249
12.0%
s249
12.0%
e249
12.0%
t249
12.0%
o166
8.0%
a166
8.0%
i166
8.0%
m166
8.0%
h83
 
4.0%
d83
 
4.0%
Other values (3)249
12.0%
Decimal Number
ValueCountFrequency (%)
296
16.5%
386
14.8%
071
12.2%
159
10.2%
957
9.8%
450
8.6%
749
8.4%
640
6.9%
840
6.9%
533
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/332
57.1%
.166
28.6%
:83
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2075
64.1%
Common1162
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/332
28.6%
.166
14.3%
296
 
8.3%
386
 
7.4%
:83
 
7.1%
071
 
6.1%
159
 
5.1%
957
 
4.9%
450
 
4.3%
749
 
4.2%
Other values (3)113
 
9.7%
Latin
ValueCountFrequency (%)
p249
12.0%
s249
12.0%
e249
12.0%
t249
12.0%
o166
8.0%
a166
8.0%
i166
8.0%
m166
8.0%
h83
 
4.0%
d83
 
4.0%
Other values (3)249
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/332
 
10.3%
p249
 
7.7%
s249
 
7.7%
e249
 
7.7%
t249
 
7.7%
o166
 
5.1%
a166
 
5.1%
i166
 
5.1%
.166
 
5.1%
m166
 
5.1%
Other values (16)1079
33.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing83
Missing (%)100.0%
Memory size792.0 B

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct8
Distinct (%)100.0%
Missing75
Missing (%)90.4%
Memory size792.0 B
https://api.tvmaze.com/episodes/2383577
https://api.tvmaze.com/episodes/2381297
https://api.tvmaze.com/episodes/2376729
https://api.tvmaze.com/episodes/2375175
https://api.tvmaze.com/episodes/2330185
Other values (3)

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters312
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2383577
2nd rowhttps://api.tvmaze.com/episodes/2381297
3rd rowhttps://api.tvmaze.com/episodes/2376729
4th rowhttps://api.tvmaze.com/episodes/2375175
5th rowhttps://api.tvmaze.com/episodes/2330185

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23835771
 
1.2%
https://api.tvmaze.com/episodes/23812971
 
1.2%
https://api.tvmaze.com/episodes/23767291
 
1.2%
https://api.tvmaze.com/episodes/23751751
 
1.2%
https://api.tvmaze.com/episodes/23301851
 
1.2%
https://api.tvmaze.com/episodes/23509161
 
1.2%
https://api.tvmaze.com/episodes/23797031
 
1.2%
https://api.tvmaze.com/episodes/23488431
 
1.2%
(Missing)75
90.4%

Length

2022-09-05T21:46:42.538495image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:42.643247image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23835771
12.5%
https://api.tvmaze.com/episodes/23812971
12.5%
https://api.tvmaze.com/episodes/23767291
12.5%
https://api.tvmaze.com/episodes/23751751
12.5%
https://api.tvmaze.com/episodes/23301851
12.5%
https://api.tvmaze.com/episodes/23509161
12.5%
https://api.tvmaze.com/episodes/23797031
12.5%
https://api.tvmaze.com/episodes/23488431
12.5%

Most occurring characters

ValueCountFrequency (%)
/32
 
10.3%
p24
 
7.7%
s24
 
7.7%
e24
 
7.7%
t24
 
7.7%
a16
 
5.1%
i16
 
5.1%
.16
 
5.1%
m16
 
5.1%
o16
 
5.1%
Other values (16)104
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter200
64.1%
Other Punctuation56
 
17.9%
Decimal Number56
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p24
12.0%
s24
12.0%
e24
12.0%
t24
12.0%
a16
8.0%
i16
8.0%
m16
8.0%
o16
8.0%
h8
 
4.0%
d8
 
4.0%
Other values (3)24
12.0%
Decimal Number
ValueCountFrequency (%)
312
21.4%
210
17.9%
79
16.1%
85
8.9%
55
8.9%
14
 
7.1%
94
 
7.1%
03
 
5.4%
62
 
3.6%
42
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/32
57.1%
.16
28.6%
:8
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin200
64.1%
Common112
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/32
28.6%
.16
14.3%
312
 
10.7%
210
 
8.9%
79
 
8.0%
:8
 
7.1%
85
 
4.5%
55
 
4.5%
14
 
3.6%
94
 
3.6%
Other values (3)7
 
6.2%
Latin
ValueCountFrequency (%)
p24
12.0%
s24
12.0%
e24
12.0%
t24
12.0%
a16
8.0%
i16
8.0%
m16
8.0%
o16
8.0%
h8
 
4.0%
d8
 
4.0%
Other values (3)24
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/32
 
10.3%
p24
 
7.7%
s24
 
7.7%
e24
 
7.7%
t24
 
7.7%
a16
 
5.1%
i16
 
5.1%
.16
 
5.1%
m16
 
5.1%
o16
 
5.1%
Other values (16)104
33.3%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing83
Missing (%)100.0%
Memory size792.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing82
Missing (%)98.8%
Memory size792.0 B
Poland

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPoland

Common Values

ValueCountFrequency (%)
Poland1
 
1.2%
(Missing)82
98.8%

Length

2022-09-05T21:46:42.737422image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:42.812127image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
poland1
100.0%

Most occurring characters

ValueCountFrequency (%)
P1
16.7%
o1
16.7%
l1
16.7%
a1
16.7%
n1
16.7%
d1
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5
83.3%
Uppercase Letter1
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1
20.0%
l1
20.0%
a1
20.0%
n1
20.0%
d1
20.0%
Uppercase Letter
ValueCountFrequency (%)
P1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P1
16.7%
o1
16.7%
l1
16.7%
a1
16.7%
n1
16.7%
d1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P1
16.7%
o1
16.7%
l1
16.7%
a1
16.7%
n1
16.7%
d1
16.7%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing82
Missing (%)98.8%
Memory size792.0 B
PL

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPL

Common Values

ValueCountFrequency (%)
PL1
 
1.2%
(Missing)82
98.8%

Length

2022-09-05T21:46:42.883147image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:42.956294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
pl1
100.0%

Most occurring characters

ValueCountFrequency (%)
P1
50.0%
L1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P1
50.0%
L1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P1
50.0%
L1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P1
50.0%
L1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing82
Missing (%)98.8%
Memory size792.0 B
Europe/Warsaw

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowEurope/Warsaw

Common Values

ValueCountFrequency (%)
Europe/Warsaw1
 
1.2%
(Missing)82
98.8%

Length

2022-09-05T21:46:43.026281image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:43.100370image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/warsaw1
100.0%

Most occurring characters

ValueCountFrequency (%)
r2
15.4%
a2
15.4%
E1
7.7%
u1
7.7%
o1
7.7%
p1
7.7%
e1
7.7%
/1
7.7%
W1
7.7%
s1
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter10
76.9%
Uppercase Letter2
 
15.4%
Other Punctuation1
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r2
20.0%
a2
20.0%
u1
10.0%
o1
10.0%
p1
10.0%
e1
10.0%
s1
10.0%
w1
10.0%
Uppercase Letter
ValueCountFrequency (%)
E1
50.0%
W1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin12
92.3%
Common1
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
r2
16.7%
a2
16.7%
E1
8.3%
u1
8.3%
o1
8.3%
p1
8.3%
e1
8.3%
W1
8.3%
s1
8.3%
w1
8.3%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r2
15.4%
a2
15.4%
E1
7.7%
u1
7.7%
o1
7.7%
p1
7.7%
e1
7.7%
/1
7.7%
W1
7.7%
s1
7.7%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing83
Missing (%)100.0%
Memory size792.0 B

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing79
Missing (%)95.2%
Memory size792.0 B
755.0
112.0
37.0
30.0

Length

Max length5
Median length4.5
Mean length4.5
Min length4

Characters and Unicode

Total characters18
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row755.0
2nd row112.0
3rd row37.0
4th row30.0

Common Values

ValueCountFrequency (%)
755.01
 
1.2%
112.01
 
1.2%
37.01
 
1.2%
30.01
 
1.2%
(Missing)79
95.2%

Length

2022-09-05T21:46:43.176627image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:43.268177image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
755.01
25.0%
112.01
25.0%
37.01
25.0%
30.01
25.0%

Most occurring characters

ValueCountFrequency (%)
05
27.8%
.4
22.2%
72
 
11.1%
52
 
11.1%
12
 
11.1%
32
 
11.1%
21
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number14
77.8%
Other Punctuation4
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
05
35.7%
72
 
14.3%
52
 
14.3%
12
 
14.3%
32
 
14.3%
21
 
7.1%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common18
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
05
27.8%
.4
22.2%
72
 
11.1%
52
 
11.1%
12
 
11.1%
32
 
11.1%
21
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
05
27.8%
.4
22.2%
72
 
11.1%
52
 
11.1%
12
 
11.1%
32
 
11.1%
21
 
5.6%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing79
Missing (%)95.2%
Memory size792.0 B
Show TV
RTL4
BBC Two
USA Network

Length

Max length11
Median length9
Mean length7.25
Min length4

Characters and Unicode

Total characters29
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowShow TV
2nd rowRTL4
3rd rowBBC Two
4th rowUSA Network

Common Values

ValueCountFrequency (%)
Show TV1
 
1.2%
RTL41
 
1.2%
BBC Two1
 
1.2%
USA Network1
 
1.2%
(Missing)79
95.2%

Length

2022-09-05T21:46:43.362180image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:43.461650image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
show1
14.3%
tv1
14.3%
rtl41
14.3%
bbc1
14.3%
two1
14.3%
usa1
14.3%
network1
14.3%

Most occurring characters

ValueCountFrequency (%)
o3
 
10.3%
w3
 
10.3%
3
 
10.3%
T3
 
10.3%
S2
 
6.9%
B2
 
6.9%
U1
 
3.4%
r1
 
3.4%
t1
 
3.4%
e1
 
3.4%
Other values (9)9
31.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter14
48.3%
Lowercase Letter11
37.9%
Space Separator3
 
10.3%
Decimal Number1
 
3.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T3
21.4%
S2
14.3%
B2
14.3%
U1
 
7.1%
N1
 
7.1%
A1
 
7.1%
C1
 
7.1%
L1
 
7.1%
R1
 
7.1%
V1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
o3
27.3%
w3
27.3%
r1
 
9.1%
t1
 
9.1%
e1
 
9.1%
h1
 
9.1%
k1
 
9.1%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin25
86.2%
Common4
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
12.0%
w3
12.0%
T3
12.0%
S2
 
8.0%
B2
 
8.0%
U1
 
4.0%
r1
 
4.0%
t1
 
4.0%
e1
 
4.0%
N1
 
4.0%
Other values (7)7
28.0%
Common
ValueCountFrequency (%)
3
75.0%
41
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII29
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3
 
10.3%
w3
 
10.3%
3
 
10.3%
T3
 
10.3%
S2
 
6.9%
B2
 
6.9%
U1
 
3.4%
r1
 
3.4%
t1
 
3.4%
e1
 
3.4%
Other values (9)9
31.0%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing79
Missing (%)95.2%
Memory size792.0 B
Turkey
Netherlands
United Kingdom
United States

Length

Max length14
Median length12
Mean length11
Min length6

Characters and Unicode

Total characters44
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowTurkey
2nd rowNetherlands
3rd rowUnited Kingdom
4th rowUnited States

Common Values

ValueCountFrequency (%)
Turkey1
 
1.2%
Netherlands1
 
1.2%
United Kingdom1
 
1.2%
United States1
 
1.2%
(Missing)79
95.2%

Length

2022-09-05T21:46:43.553418image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:43.652057image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
united2
33.3%
turkey1
16.7%
netherlands1
16.7%
kingdom1
16.7%
states1
16.7%

Most occurring characters

ValueCountFrequency (%)
e6
13.6%
t5
11.4%
n4
 
9.1%
d4
 
9.1%
i3
 
6.8%
U2
 
4.5%
r2
 
4.5%
2
 
4.5%
a2
 
4.5%
s2
 
4.5%
Other values (12)12
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter36
81.8%
Uppercase Letter6
 
13.6%
Space Separator2
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e6
16.7%
t5
13.9%
n4
11.1%
d4
11.1%
i3
8.3%
r2
 
5.6%
a2
 
5.6%
s2
 
5.6%
m1
 
2.8%
o1
 
2.8%
Other values (6)6
16.7%
Uppercase Letter
ValueCountFrequency (%)
U2
33.3%
K1
16.7%
T1
16.7%
N1
16.7%
S1
16.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin42
95.5%
Common2
 
4.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e6
14.3%
t5
11.9%
n4
 
9.5%
d4
 
9.5%
i3
 
7.1%
U2
 
4.8%
r2
 
4.8%
a2
 
4.8%
s2
 
4.8%
m1
 
2.4%
Other values (11)11
26.2%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII44
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e6
13.6%
t5
11.4%
n4
 
9.1%
d4
 
9.1%
i3
 
6.8%
U2
 
4.5%
r2
 
4.5%
2
 
4.5%
a2
 
4.5%
s2
 
4.5%
Other values (12)12
27.3%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing79
Missing (%)95.2%
Memory size792.0 B
TR
NL
GB
US

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowTR
2nd rowNL
3rd rowGB
4th rowUS

Common Values

ValueCountFrequency (%)
TR1
 
1.2%
NL1
 
1.2%
GB1
 
1.2%
US1
 
1.2%
(Missing)79
95.2%

Length

2022-09-05T21:46:43.739082image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:43.833336image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
tr1
25.0%
nl1
25.0%
gb1
25.0%
us1
25.0%

Most occurring characters

ValueCountFrequency (%)
T1
12.5%
R1
12.5%
N1
12.5%
L1
12.5%
G1
12.5%
B1
12.5%
U1
12.5%
S1
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter8
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T1
12.5%
R1
12.5%
N1
12.5%
L1
12.5%
G1
12.5%
B1
12.5%
U1
12.5%
S1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
T1
12.5%
R1
12.5%
N1
12.5%
L1
12.5%
G1
12.5%
B1
12.5%
U1
12.5%
S1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T1
12.5%
R1
12.5%
N1
12.5%
L1
12.5%
G1
12.5%
B1
12.5%
U1
12.5%
S1
12.5%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing79
Missing (%)95.2%
Memory size792.0 B
Europe/Istanbul
Europe/Amsterdam
Europe/London
America/New_York

Length

Max length16
Median length15.5
Mean length15
Min length13

Characters and Unicode

Total characters60
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowEurope/Istanbul
2nd rowEurope/Amsterdam
3rd rowEurope/London
4th rowAmerica/New_York

Common Values

ValueCountFrequency (%)
Europe/Istanbul1
 
1.2%
Europe/Amsterdam1
 
1.2%
Europe/London1
 
1.2%
America/New_York1
 
1.2%
(Missing)79
95.2%

Length

2022-09-05T21:46:43.932763image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:44.031503image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/istanbul1
25.0%
europe/amsterdam1
25.0%
europe/london1
25.0%
america/new_york1
25.0%

Most occurring characters

ValueCountFrequency (%)
r6
 
10.0%
o6
 
10.0%
e6
 
10.0%
u4
 
6.7%
/4
 
6.7%
E3
 
5.0%
p3
 
5.0%
m3
 
5.0%
a3
 
5.0%
n3
 
5.0%
Other values (15)19
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter46
76.7%
Uppercase Letter9
 
15.0%
Other Punctuation4
 
6.7%
Connector Punctuation1
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r6
13.0%
o6
13.0%
e6
13.0%
u4
8.7%
p3
 
6.5%
m3
 
6.5%
a3
 
6.5%
n3
 
6.5%
d2
 
4.3%
t2
 
4.3%
Other values (7)8
17.4%
Uppercase Letter
ValueCountFrequency (%)
E3
33.3%
A2
22.2%
Y1
 
11.1%
N1
 
11.1%
L1
 
11.1%
I1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
/4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin55
91.7%
Common5
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
r6
 
10.9%
o6
 
10.9%
e6
 
10.9%
u4
 
7.3%
E3
 
5.5%
p3
 
5.5%
m3
 
5.5%
a3
 
5.5%
n3
 
5.5%
d2
 
3.6%
Other values (13)16
29.1%
Common
ValueCountFrequency (%)
/4
80.0%
_1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r6
 
10.0%
o6
 
10.0%
e6
 
10.0%
u4
 
6.7%
/4
 
6.7%
E3
 
5.0%
p3
 
5.0%
m3
 
5.0%
a3
 
5.0%
n3
 
5.0%
Other values (15)19
31.7%

_embedded.show.network.officialSite
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing82
Missing (%)98.8%
Memory size792.0 B
https://www.bbc.co.uk/bbctwo

Length

Max length28
Median length28
Mean length28
Min length28

Characters and Unicode

Total characters28
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttps://www.bbc.co.uk/bbctwo

Common Values

ValueCountFrequency (%)
https://www.bbc.co.uk/bbctwo1
 
1.2%
(Missing)82
98.8%

Length

2022-09-05T21:46:44.108481image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:46:44.182840image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.bbc.co.uk/bbctwo1
100.0%

Most occurring characters

ValueCountFrequency (%)
w4
14.3%
b4
14.3%
t3
10.7%
/3
10.7%
.3
10.7%
c3
10.7%
o2
7.1%
h1
 
3.6%
p1
 
3.6%
s1
 
3.6%
Other values (3)3
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter21
75.0%
Other Punctuation7
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w4
19.0%
b4
19.0%
t3
14.3%
c3
14.3%
o2
9.5%
h1
 
4.8%
p1
 
4.8%
s1
 
4.8%
u1
 
4.8%
k1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/3
42.9%
.3
42.9%
:1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin21
75.0%
Common7
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w4
19.0%
b4
19.0%
t3
14.3%
c3
14.3%
o2
9.5%
h1
 
4.8%
p1
 
4.8%
s1
 
4.8%
u1
 
4.8%
k1
 
4.8%
Common
ValueCountFrequency (%)
/3
42.9%
.3
42.9%
:1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w4
14.3%
b4
14.3%
t3
10.7%
/3
10.7%
.3
10.7%
c3
10.7%
o2
7.1%
h1
 
3.6%
p1
 
3.6%
s1
 
3.6%
Other values (3)3
10.7%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing83
Missing (%)100.0%
Memory size792.0 B

Interactions

2022-09-05T21:46:26.605689image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:18.723578image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.633806image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.415806image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.199218image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.979787image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.760417image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.547768image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.340073image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.073019image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.835075image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.683907image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:18.894196image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.709570image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.494195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.272391image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.056026image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.840543image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.622393image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.409350image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.143284image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.906830image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.754090image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:18.973548image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.780678image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.565295image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.348854image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.131576image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.914593image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.698855image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.476783image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.216644image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.977581image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.822982image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.046796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.854650image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.634992image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.416892image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.207793image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.983778image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.770747image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.549687image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.285591image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.050750image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.896059image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.122330image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.924346image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.709150image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.486887image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.278085image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.060855image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.840494image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.615092image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.357159image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.121420image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.962785image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.197514image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.992815image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.777413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.560751image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.346084image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.128311image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.914241image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.679027image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.426928image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.189010image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:27.034936image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.268341image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.067188image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.845578image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.630981image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.420670image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.197910image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.984477image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.749232image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.495005image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.264391image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:27.109168image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.339089image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.137895image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.921564image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.701196image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.490056image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.274502image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.057355image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.815333image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.564365image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.333920image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:27.171813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.411518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.203454image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.987028image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.771885image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.553593image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.338022image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.127035image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.875363image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.631287image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.397354image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:27.237338image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.483413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.274559image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.057276image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.838165image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.624368image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.403620image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.195706image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.943506image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.695933image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.468062image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:27.308063image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:19.558975image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:20.345051image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.130683image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:21.906975image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:22.692026image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:23.479502image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:24.266454image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.008959image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:25.765493image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:46:26.538656image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:46:44.269665image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:46:44.500456image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:46:44.723255image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:46:44.988458image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:46:27.669907image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:46:28.404618image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:46:28.941986image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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01977899https://www.tvmaze.com/episodes/1977899/obycnaa-zensina-2x03-seria-12Серия 1223.0regular2020-12-2110:002020-12-20T22:00:00+00:0055.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726673.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726673.jpghttps://api.tvmaze.com/episodes/197789939115https://www.tvmaze.com/shows/39115/obycnaa-zensinaОбычная женщинаScriptedRussian[Drama, Crime, Mystery]Ended50.048.02018-10-292021-01-07https://premier.one/show/840522:00[Monday, Tuesday, Wednesday, Thursday]7.739NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaN345280.0tt8561620https://static.tvmaze.com/uploads/images/medium_portrait/289/722910.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/722910.jpg<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>1610110841https://api.tvmaze.com/shows/39115https://api.tvmaze.com/episodes/1977905NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
12164195https://www.tvmaze.com/episodes/2164195/ispoved-1x09-viktoria-bonaВиктория Боня19.0regular2020-12-2112:002020-12-21T00:00:00+00:0048.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/216419548683https://www.tvmaze.com/shows/48683/ispovedИсповедьDocumentaryRussian[]Ended48.047.02020-05-112022-08-30https://premier.one/collections/13412:00[Monday]NaN34NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/713049.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713049.jpg<p>This is not an interview, this is a confession. Revelations of the artist in the form of a monologue. The guest's opinion may not coincide with the opinion of the PREMIER platform editorial board.</p>1662030100https://api.tvmaze.com/shows/48683https://api.tvmaze.com/episodes/2383519NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21982407https://www.tvmaze.com/episodes/1982407/volk-1x09-seria-09Серия 0919.0regular2020-12-212020-12-21T00:00:00+00:0051.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198240752181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian[Drama, Adventure, Mystery]Ended51.050.02020-12-072020-12-28https://premier.one/show/12339[Monday, Thursday]NaN24NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpgNone1640435531https://api.tvmaze.com/shows/52181https://api.tvmaze.com/episodes/1982412NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31982408https://www.tvmaze.com/episodes/1982408/volk-1x10-seria-10Серия 10110.0regular2020-12-212020-12-21T00:00:00+00:0051.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198240852181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian[Drama, Adventure, Mystery]Ended51.050.02020-12-072020-12-28https://premier.one/show/12339[Monday, Thursday]NaN24NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpgNone1640435531https://api.tvmaze.com/shows/52181https://api.tvmaze.com/episodes/1982412NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
41988014https://www.tvmaze.com/episodes/1988014/muzskaa-tema-1x03-seria-3Серия 313.0regular2020-12-2112:002020-12-21T00:00:00+00:0030.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198801452520https://www.tvmaze.com/shows/52520/muzskaa-temaМужская темаTalk ShowRussian[]Ended30.030.02020-12-172020-12-25https://www.ivi.ru/watch/muzhskaya-tema12:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN3NaN337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/289/723328.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/723328.jpg<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>1616722619https://api.tvmaze.com/shows/52520https://api.tvmaze.com/episodes/1988016NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52062926https://www.tvmaze.com/episodes/2062926/god-of-ten-thousand-realms-1x01-episode-1Episode 111.0regular2020-12-2110:002020-12-21T02:00:00+00:007.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/206292654541https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realmsGod of Ten Thousand RealmsAnimationChinese[Adventure, Anime, Fantasy]Running7.07.02020-12-21Nonehttps://v.qq.com/detail/m/mzc002007995z4v.html10:00[Monday, Friday]NaN36NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN394467.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/320/800829.jpghttps://static.tvmaze.com/uploads/images/original_untouched/320/800829.jpg<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>1642689319https://api.tvmaze.com/shows/54541https://api.tvmaze.com/episodes/2261133NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
62062927https://www.tvmaze.com/episodes/2062927/god-of-ten-thousand-realms-1x02-episode-2Episode 212.0regular2020-12-2110:002020-12-21T02:00:00+00:007.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/206292754541https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realmsGod of Ten Thousand RealmsAnimationChinese[Adventure, Anime, Fantasy]Running7.07.02020-12-21Nonehttps://v.qq.com/detail/m/mzc002007995z4v.html10:00[Monday, Friday]NaN36NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN394467.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/320/800829.jpghttps://static.tvmaze.com/uploads/images/original_untouched/320/800829.jpg<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>1642689319https://api.tvmaze.com/shows/54541https://api.tvmaze.com/episodes/2261133NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
72062928https://www.tvmaze.com/episodes/2062928/god-of-ten-thousand-realms-1x03-episode-3Episode 313.0regular2020-12-2110:002020-12-21T02:00:00+00:007.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/206292854541https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realmsGod of Ten Thousand RealmsAnimationChinese[Adventure, Anime, Fantasy]Running7.07.02020-12-21Nonehttps://v.qq.com/detail/m/mzc002007995z4v.html10:00[Monday, Friday]NaN36NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN394467.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/320/800829.jpghttps://static.tvmaze.com/uploads/images/original_untouched/320/800829.jpg<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>1642689319https://api.tvmaze.com/shows/54541https://api.tvmaze.com/episodes/2261133NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
82140388https://www.tvmaze.com/episodes/2140388/going-seventeen-2020-12-21-going-vs-seventeen-2GOING VS SEVENTEEN #2202043.0regular2020-12-212020-12-21T03:00:00+00:0030.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/214038856655https://www.tvmaze.com/shows/56655/going-seventeenGoing SeventeenVarietyKorean[]Running30.030.02017-06-12NoneNone08:00[Wednesday]NaN69NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNaNNaN330462.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/394/985825.jpghttps://static.tvmaze.com/uploads/images/original_untouched/394/985825.jpg<p>Initially a series of behind-the-scenes vlogs, <b>Going Seventeen</b> has taken a more structured route since mid-2019 and is now a reality-variety show with themed episodes. Every week, the members of Seventeen play games or participate in a variety of activities for everyone's delight and entertainment. Season 2021's keyword is "Watch What You Say", meaning that anything the members say can and will be turned into content...</p>1662048054https://api.tvmaze.com/shows/56655https://api.tvmaze.com/episodes/2383576NaNhttps://api.tvmaze.com/episodes/2383577NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92353914https://www.tvmaze.com/episodes/2353914/300-year-old-class-of-2020-1x01-episode-1Episode 111.0regular2020-12-212020-12-21T03:00:00+00:0012.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/235391462764https://www.tvmaze.com/shows/62764/300-year-old-class-of-2020300 Year-Old Class of 2020ScriptedKorean[Comedy, Fantasy, History]EndedNaN15.02020-12-212020-12-28None[Monday]NaN50NaN30.0Naver TVCastKorea, Republic ofKRAsia/Seoulhttps://tv.naver.com/NaNNaN410187.0tt14125832https://static.tvmaze.com/uploads/images/medium_portrait/414/1035476.jpghttps://static.tvmaze.com/uploads/images/original_untouched/414/1035476.jpg<p>The series is a fantasy comic web drama that tells a story of three students, who were studying in Seowon during the Joseon period accidently time travel and arrive at present-day Seowon in 2020.</p>1656357007https://api.tvmaze.com/shows/62764https://api.tvmaze.com/episodes/2353919NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

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731969063https://www.tvmaze.com/episodes/1969063/rooster-teeth-podcast-2020-12-21-okay-lunar-628Okay Lunar - #628202051.0regular2020-12-212020-12-21T17:00:00+00:0090.0<p>Join Gus Sorola, Gavin Free, Drew Saplin, and Barbara Dunkelman as they discuss Drew's hate for the moon, astrology, climbing very tall mountains and bouncing, and more on this week's RT Podcast!</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/343/857759.jpghttps://static.tvmaze.com/uploads/images/original_untouched/343/857759.jpghttps://api.tvmaze.com/episodes/19690636146https://www.tvmaze.com/shows/6146/rooster-teeth-podcastRooster Teeth PodcastTalk ShowEnglish[Comedy]Running90.090.02008-12-09Nonehttps://roosterteeth.com/series/rt-podcast[Monday, Tuesday]NaN33NaN32.0Rooster TeethUnited StatesUSAmerica/New_YorkNoneNaNNaN264458.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/23/59538.jpghttps://static.tvmaze.com/uploads/images/original_untouched/23/59538.jpg<p>On a more or less weekly basis the Rooster Teeth (creators of Red vs. Blue) crew discuss gaming, films and projects that they are currently working on.</p>1662130641https://api.tvmaze.com/shows/6146https://api.tvmaze.com/episodes/2383945NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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801988884https://www.tvmaze.com/episodes/1988884/upstart-crow-s03-special-lockdown-christmas-1603Lockdown Christmas 16033NaNsignificant_special2020-12-2121:002020-12-21T21:00:00+00:0030.0<p>The plague has hit London, and as Christmas approaches, Will and Kate are in wave fifteen of state-enforced home confinement together in Will's London lodgings.</p>8.5https://static.tvmaze.com/uploads/images/medium_landscape/291/728689.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/728689.jpghttps://api.tvmaze.com/episodes/19888849815https://www.tvmaze.com/shows/9815/upstart-crowUpstart CrowScriptedEnglish[Comedy]To Be Determined30.030.02016-05-09Nonehttp://www.bbc.co.uk/programmes/b0959g2621:00[Wednesday]7.681NaNNaNNaNNaNNaNNaNNaNNaNNaN309790.0tt4793190https://static.tvmaze.com/uploads/images/medium_portrait/57/142763.jpghttps://static.tvmaze.com/uploads/images/original_untouched/57/142763.jpg<p>Comedy about William Shakespeare as he starts to make a name for himself in London while also trying to be a good husband and father for his family in Stratford-upon-Avon.</p>1658531810https://api.tvmaze.com/shows/9815https://api.tvmaze.com/episodes/1988884NaNNaNNaNNaNNaNNaNNaN37.0BBC TwoUnited KingdomGBEurope/Londonhttps://www.bbc.co.uk/bbctwoNaN
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